data scientist

Jerry

<div><div><p><b>Why We Exist</b></p>
<p>Your car and your home are your most important assets, yet the experience of owning them is stuck in the 90s. Every part of the journey &mdash; buy/sell, insurance, maintenance, repairs &mdash; is fragmented, complicated, and expensive.</p><br>
<div></div><p>Jerry.ai is building the first app to manage it all. We started with car insurance in 2019, became one of the top 3 brokers in the U.S., then added driving insights, diagnostics, and a repair marketplace.</p><br>
<div></div><p>We've reached 5M+ customers, raised $240M+, scaled revenue 70X, and became profitable in early 2024. We're now expanding into adjacent verticals (e.g. home, motorcycle, RV, etc) to become the one-stop-shop for all your physical assets.</p><br>
<div></div><p><b>Why We&rsquo;re Hiring</b></p>
<p>Our Data Science &amp; Analytics team has been a force multiplier and accelerant to our business that has helped us reach these pivotal milestones in spite of headwinds and within a highly competitive market. They are a team of former McKinsey, BCG and Bain consultants who drive data &amp; insights, and inform decision-making across every corner of our business. They are analytical powerhouses and first principles problem solvers who push forward our most important initiatives across product, growth, tech, and operations.</p><br>
<div></div><p>Every business unit has a Data Science team member embedded within it &mdash; someone who doesn't just run analyses and build dashboards, but shapes what questions we should ask, what data to pull, what conclusions to draw, what decisions to make, and then drives our teams towards our next goal: go from 5M to 50M customers and become a $10B business in the next 4 years.</p><br>
<div></div><p>As our business continues to expand, there is growing demand for more Data Science team members. We are hiring 4-6 people to drive impact in these areas:</p>
<ul><li><p>Growth Marketing</p>
</li><li><p>Product Development</p>
</li><li><p>AI &amp; Automation</p>
</li><li><p>Strategic Partnerships</p><br>
</li></ul><div></div><p><b>On leveling: </b>You may see job ads for this role at different job levels. Our priority is finding the right people, we can be flexible with job title/leveling.</p><br>
<div></div><p><b>Why You Will (Or Won't) Like Working Here</b></p>
<ul><li><p><b>No slides:</b> If you've worked in consulting, you know what it feels like to be up at 3am reformatting a deck. That doesn't exist here. The only work that gets done at Jerry is work that will materially change the trajectory of our business &mdash; an important product, a new growth channel, a key metric, a critical partner relationship, etc.</p>
</li><li><p><b>No corporate fluff:</b> The Data Science &amp; Analytics team is 14 insatiable learners who care deeply about solving difficult problems and making a tangible impact. Every person owns a critical domain. There is no bloat, unnecessary meetings, or waiting for approvals.</p>
</li><li><p><b>Hands-on: </b>This is not a pure strategy role, you will also own execution. Your day-to-day will be surfacing analytical insights, driving decisions, and seeing them through end-to-end.</p><br>
</li></ul><div></div><p><b>What You'll Own</b></p>
<p>You'll sit on our central Data Science &amp; Analytics team but you&rsquo;ll be embedded in one of Jerry's core business areas &mdash; growth, product, AI and automation, strategic partnerships &mdash; and own the analytical function for that business unit end-to-end.</p>
<ul><li><p><b>Define the right problems: </b>Before any analysis, understand what business question it's answering and what decision it will inform. Push back if the question is flawed.</p>
</li><li><p><b>Data and insights: </b>Define metrics, build reports, run analyses, design experiments, and surface data insights that move your team's key metrics.</p>
</li><li><p><b>Drive outcomes: </b>Bring recommendations to your counterparts in product, growth, finance or operations, tell them what's happening and why, and what next steps should be.</p><br>
</li></ul><div></div><p><b>Who You Are</b></p>
<ul><li><p><b>First principles thinker: </b>You break ambiguous problems into clear hypotheses before touching data. You're analytically strong (comfortable with SQL or Python) but your instinct is to ask &quot;what are we trying to solve here?&quot; before jumping to &quot;what should I build?&quot;</p>
</li><li><p><b>Direct communicator:</b> You can walk a skeptical stakeholder through a complex finding and get buy-in quickly. You write clearly, speak precisely, and don't bury the lede.</p>
</li><li><p><b>Owner: </b>You act like your name is on the door. If something is broken, you feel responsible for fixing it, even if it&rsquo;s outside of your swim lane.</p><br>
</li></ul><div></div><p><b>What You'll Bring</b></p>
<ul><li><p>2+ years of experience at a consulting firm, investment bank, or high-growth technology company.</p>
</li><li><p>Strong analytical skills; ability to pull, structure, and interpret data independently.</p>
</li><li><p>Track record of owning ambiguous problems and delivering impact.</p>
</li><li><p>Clear, persuasive communicator who can influence decisions at the leadership level.</p><br>
</li></ul><div></div><p><b>Our Tools</b></p>
<p>SQL (Clickhouse), Metabase, Python, Jupyter Hub, GitHub.</p><div><br>
</div><div></div><p><i>While we appreciate your interest and application, only applicants under consideration will be contacted.</i></p>
<p></p><p><i>Jerry.ai is proud to be an Equal Employment Opportunity employer. We prohibit discrimination based on race, religion, color, national origin, sex, pregnancy, reproductive health decisions or related medical conditions, sexual orientation, gender identity, gender expression, age, veteran status, disability, genetic information, or other characteristics protected by applicable local, state or federal laws.
</i></p><p></p><p><i>Jerry.ai is committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, please contact us at </i><i>recruiting@jerry.ai</i></p>
<p></p><p><i>The successful candidate&rsquo;s starting pay will fall within the pay range listed on this job posting, determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation may include opportunities for equity grants.
</i></p><p></p><p><i>We offer a comprehensive benefits package to regular employees, including health, dental, and vision coverage, paid time off, paid parental leave, 401(K) plan with employer matching, and wellness benefits, among others. Equity opportunities may also be part of your total rewards package. Part-time, contract, or freelance roles may not be eligible for certain benefits.</i></p>
<p></p><p><b>About Jerry.ai</b></p>
<p>Jerry.ai is America&rsquo;s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets.</p>
<p></p><p>Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. We spend every day innovating and improving our AI-powered app to provide the best possible experience for our customers. From car insurance and financing to maintenance and safety, Jerry.ai does it all.</p>
<p></p><p>We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. We have more than 5 million customers &mdash; and we&rsquo;re just getting started.</p>
<p></p><p>Jerry.ai was founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing.</p>
<p></p><p>Join our team and work with passionate, curious and egoless people who love solving real-world problems. Help us build a revolutionary product that&rsquo;s disrupting a massive market.</p></div></div><p></p>

Data Scientist

Aircall

<p></p><div><div><p><div><div><div><b>New York Office</b></div><div><b>Engineering &ndash; 13008 - Data /</b></div><div><b>Permanent Full Time Employee /</b></div><div><b>Hybrid</b></div></div></div><p>
</p></p></div><div><div><div>
Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We&rsquo;re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.</div>
<div></div>
<div>Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall&rsquo;s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.</div>
<div></div>
<div>Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We&rsquo;ve built a product customers love and a business that&rsquo;s scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines.</div>
<div>At Aircall, you&rsquo;ll join a company in motion. We&rsquo;re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.</div>
<div></div>
<div><b>How we work at Aircall: </b>We&rsquo;re customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you&rsquo;ll feel at home here.</div><div></div><div><br>
<div><b>
About the role
</b></div><div>The Data Engineering team at Aircall works on providing high-quality, reliable, and actionable data. As an AI-first data team, we are currently in a pivotal transition to build a robust semantic layer that will power our AI-first data platform, enabling analytics at speed and democratizing intelligent insights across the company. Some of the key problems we are currently solving include taking charge of data reliability, integrating new sources for raw data ingestion, and building sophisticated data models to power real-time dashboards and predictive analytics.</div>
<div></div>
<div>In this role, you will be instrumental in building new datasets for high-impact use cases such as churn prediction and feature adoption, while owning the end-to-end reliability and scalability of our data pipelines. You will work closely with Product and GTM business teams, sitting at the heart of a larger data organization alongside Data Science, Analytics, and Applied Scientists to bridge the gap between raw data and AI-driven decision-making.</div>
</div></div><div><div><h3 class="jobSectionHeader"><b>Your missions @ Aircall:</b></h3><div><div><div>
<ul><li>Partner with GTM stakeholders to translate business questions into reliable, scalable data products.</li>
<li>Provide actionable insights and compelling narratives to influence major decisions at the C-level.</li>
<li>Build and own reporting in Looker, from LookML development to dashboard performance optimization, powering self-service analytics GTM teams rely on every day.</li>
<li>Work closely with data engineers to continuously improve the data stack, governance practices, and analysis quality.</li>
</ul></div></div></div></div></div><div><div><h3 class="jobSectionHeader"><b>A little more about you:</b></h3><div><div><div>
<ul><li>2+ years of hands-on experience in a high growth environment</li>
<li>Proficiency in SQL for deriving insights</li>
<li>Proficiency in Python</li>
<li>Hands-on Looker/LookML experience</li>
<li>Excellent interpersonal skills and the ability to explain complex data clearly to stakeholders at all levels</li>
<li>You have an insatiable curiosity and are biased toward action</li>
</ul></div></div></div></div></div><div><div>$140,000 - $180,000 a year</div><div>
This is not including equity and other benefits. The actual salary offered will carefully consider a wide range of factors, including your skills, qualifications, and experience.</div></div><div><div><b>
Why join us?</b></div>
<div></div>
<div>   Key moment to join Aircall in terms of growth and opportunities</div>
<ul><li>️ Our people matter, work-life balance is important at Aircall</li></ul>
<div>   Fast-learning environment, entrepreneurial and strong team spirit</div>
<div>   45+ Nationalities: cosmopolite &amp; multi-cultural mindset</div>
<div>   Competitive salary package &amp; benefits</div>
<div>   Medical, dental, and vision insurance is 100% covered</div>
<div>   401k plan with company matching!</div>
<div>✈️ Unlimited PTO &mdash; take the time you need to come to work feeling great!</div>
<ul><li>️ Wellness, commuter, and childcare reimbursements</li></ul>
<div>   Generous parental leave policy</div>
<div></div>
<div>DE&amp;I Statement:</div>
<div>At Aircall, we believe diversity, equity and inclusion &ndash; irrespective of origins, identity, background and orientations &ndash; are core to our journey.</div>
<div></div>
<div>We pride ourselves on promoting active inclusion within our business to foster a strong sense of belonging for all. We&rsquo;re working to create a place filled with diverse people who can enrich and learn from one another. We&rsquo;re committed to ensuring that everyone not only has a seat at the table but is valued and respected at it by providing equal opportunities to develop and thrive.</div>
<div></div>
<div>We will constantly challenge ourselves to make sure that we live up to our ambitions around diversity, equity and inclusion, and keep this conversation open. Above all else, we understand and acknowledge that we have work to do and much to learn.</div>
<div></div>
<div>Want to know more about candidate privacy? Find our Candidate Privacy Notice here.</div></div><div><div><i>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</i></div></div></div></div><p></p>

Fusemachines

<div>
 <strong>
  About Fusemachines
  <br/>
  <br/>
 </strong>
 Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 <br/>
 <br/>
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 <br/>
 <br/>
 <strong>
  Type: Full-time, Remote
  <br/>
  <br/>
 </strong>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We&rsquo;re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You&rsquo;ll work across the ML lifecycle&mdash;from problem framing and data exploration to model development, evaluation, deployment, and monitoring&mdash;often in partnership with client stakeholders and internal delivery teams.
 <br/>
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 You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production-ready systems.
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 <br/>
 <strong>
  Key Responsibilities
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  <br/>
 </strong>
 <ul>
  <li>
   Problem Framing &amp; Stakeholder Partnership
  </li>
  <ul>
   <li>
    Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)
   </li>
   <li>
    Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)
   </li>
  </ul>
  <li>
   Data Analysis &amp; Feature Engineering
  </li>
  <ul>
   <li>
    Use SQL and Python to extract, join, and analyze data from relational databases and data warehouses
   </li>
   <li>
    Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices
   </li>
   <li>
    Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions
   </li>
  </ul>
  <li>
   Model Development (Core ML)
  </li>
  <ul>
   <li>
    Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)
   </li>
   <li>
    Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation
   </li>
   <li>
    Build time series models (statistical and ML/DL approaches) and validate with proper backtesting
   </li>
   <li>
    Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness
   </li>
   <li>
    Apply statistics in practice (hypothesis testing, confidence intervals, sampling, experiment design) to support inference and decision-making
   </li>
  </ul>
  <li>
   Deep Learning
  </li>
  <ul>
   <li>
    Build and train deep learning models using PyTorch or TensorFlow/Keras
   </li>
   <li>
    Use best practices for training (regularization, calibration, class imbalance handling, reproducibility, sound train/val/test design)
   </li>
  </ul>
  <li>
   Evaluation, Explainability, and Iteration
  </li>
  <ul>
   <li>
    Choose appropriate metrics (AUC/F1/PR, RMSE/MAE/MAPE, calibration, lift, and business KPIs) and create evaluation reports
   </li>
   <li>
    Perform error analysis and interpretation (feature importance/SHAP, cohort slicing) and iterate based on evidence
   </li>
  </ul>
  <li>
   Productionization &amp; MLOps (Project-Dependent)
  </li>
  <ul>
   <li>
    Package models for deployment (batch scoring pipelines or real-time APIs) and collaborate with engineers on integration
   </li>
   <li>
    Implement practical MLOps: versioning, reproducible training, automated evaluation, monitoring for drift/performance, and retraining plans
   </li>
  </ul>
  <li>
   Documentation &amp; Communication
  </li>
  <ul>
   <li>
    Communicate tradeoffs and recommendations clearly to technical and non-technical stakeholders
   </li>
   <li>
    Create documentation and lightweight demos that make results actionable
    <br/>
   </li>
  </ul>
 </ul>
 Success in This Role Looks Like
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  <li>
   You deliver models that perform well and move business metrics (revenue lift, cost reduction, risk reduction, improved forecast accuracy, operational efficiency)
  </li>
  <li>
   Your work is reproducible and production-aware: clear data lineage, robust evaluation, and a credible path to deployment/monitoring
  </li>
  <li>
   Stakeholders trust your judgment in selecting methods and communicating uncertainty honestly
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   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
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 <ul>
  <li>
   3&ndash;8 years of experience in data science, machine learning engineering, or applied ML (mid-to-senior)
  </li>
  <li>
   Strong Python skills for data analysis and modeling (pandas/numpy/scikit-learn or equivalent)
  </li>
  <li>
   Strong SQL skills (joins, window functions, aggregation, performance awareness)
  </li>
  <li>
   Solid foundation in statistics (hypothesis testing, uncertainty, bias/variance, sampling) and practical experimentation mindset
  </li>
  <li>
   Hands-on experience across multiple model types, including:
  </li>
  <ul>
   <li>
    Classification &amp; regression
   </li>
   <li>
    Time series forecasting
   </li>
   <li>
    Clustering/segmentation
   </li>
  </ul>
  <li>
   Experience with deep learning in PyTorch or TensorFlow/Keras
  </li>
  <li>
   Strong problem-solving skills: ability to work with ambiguous goals and messy data
  </li>
  <li>
   Clear communication skills and ability to translate analysis into decisions
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
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 </strong>
 <ul>
  <li>
   Experience with Databricks for applied ML (e.g., Spark, Delta Lake, MLflow, Databricks Jobs/Workflows)
  </li>
  <li>
   Experience deploying models to production (APIs, batch pipelines) and maintaining them over time (monitoring, retraining)
  </li>
  <li>
   Experience with orchestration tools (Airflow, Prefect, Dagster) and modern data stacks (Snowflake/BigQuery/Redshift/Databricks)
  </li>
  <li>
   Experience with cloud platforms (AWS/GCP/Azure/IBM) and containerization (Docker)
  </li>
  <li>
   Experience with responsible AI and governance best practices (privacy/PII handling, auditability, access controls)
  </li>
  <li>
   Consulting or client-facing delivery experience
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Certifications (Strong Plus)
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  <br/>
 </strong>
 Candidates with at least one relevant certification are especially encouraged to apply:
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  <li>
   Cloud certifications: AWS, Google Cloud, Microsoft Azure, or IBM (data/AI/ML tracks)
  </li>
  <li>
   Databricks certifications (Data Scientist, Data Engineer, or related)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice-to-Have
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 </strong>
 <ul>
  <li>
   Causal inference experience (e.g., quasi-experimental methods, propensity scores, uplift/heterogeneous treatment effects, experimentation beyond A/B tests)
  </li>
  <li>
   Agentic development experience: designing and evaluating agentic workflows (tool use, planning, memory/state, guardrails) and integrating them into products
  </li>
  <li>
   Deep familiarity with agentic coding tools and workflows for accelerated product development (e.g., AI-assisted IDEs, code agents, automated testing/refactoring, repo-aware assistants), including strong judgment on quality, security, and maintainability
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  <em>
   Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
   <br/>
   <br/>
  </em>
 </em>
 Important: Immigration Sponsorship Policy
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 <br/>
 Fusemachines is unable to proceed with candidates who require any form of work authorization or immigration support from the company. This restriction applies to all types of support, including:
 <br/>
 <br/>
 <ul>
  <li>
   Direct Company Sponsorship: Such as H-1B, J-1, or TN visas
  </li>
  <li>
   Employer of Record: Listing Fusemachines as the immigration employer on any government documentation
  </li>
  <li>
   Written Documentation: Providing letters or other support for any work authorization (e.g., OPT, STEM OPT, CPT)
   <br/>
   <br/>
  </li>
 </ul>
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Machine Learning Engineer / Data Scientist

Nomura

<div></div><div><div><div><div><div>Job Code: 13473
</div></div></div></div><div><div><div><div>Country: US
</div></div></div></div><div><div><div><div>City: New York
</div></div></div></div><div><div><div><div>Skill Category: Internal Audit
</div></div></div></div><div><div><div><div>Description:
<h3 class="jobSectionHeader"><b>Corporate Title: </b>Associate</h3>
<h3 class="jobSectionHeader"><b>Department:</b> Internal Audit</h3>
<h3 class="jobSectionHeader"><b>Location: </b>New York, NY</h3>
<h3 class="jobSectionHeader">The base pay range for this position at commencement of employment is expected to be between $130,000 and $150,000 per year. .</h3><br>
<div></div><div><b>Company overview</b></div>
<p>Nomura is a global financial services group with an integrated network spanning approximately 30 countries and regions. By connecting markets East &amp; West, Nomura services the needs of individuals, institutions, corporates and governments through its three business divisions: Wealth Management, Investment Management, and Wholesale (Global Markets and Investment Banking). Founded in 1925, the firm is built on a tradition of disciplined entrepreneurship, serving clients with creative solutions and considered thought leadership. For further information about Nomura, visit www.nomura.com.</p><br>
<div></div><div>Aon&rsquo;s Benefit Index&reg;: Nomura&rsquo;s benefits <b>rank</b> <b>#1</b> amongst our competitors.</div><br>
<p></p><p><b>Department overview</b><b>:</b></p>
<p>The Internal Audit department is a key part of Nomura&rsquo;s corporate governance and the department&rsquo;s primary objectives are to review the company's control environment and report any weaknesses identified to the Audit Committee and senior management.
</p><p>The Internal Audit department has over 190 staff that are located in major cities around the world. The Nomura Global Wholesale Internal Audit department in the Americas comprises 40 professionals, split across Trading, Sales and Investment Banking businesses as well as Technology, Risk Management, Legal and Compliance and Finance specialists, reporting to the Americas Head of Internal Audit.</p><br>
<p></p><p><b>Key responsibilities;</b></p>
<p>Reporting to the Americas Global Markets Audit Technology Portfolio Director who is responsible for the Global Equities and Securitized Products IT audit portfolio globally, the Global Markets Internal Audit Data Scientist will be responsible for working as part of an integrated team to audit Global Markets businesses.
</p><p>The role involves working with technology and control stakeholders to understand and assess the technology risks across a range of products and make value added control improvement recommendations to senior management. The role covers systems supporting structured and complex businesses as well as vanilla businesses across all major asset classes (Credit, Rates, FX, and Equities).</p>
<p>The role involves using data analytics and developing automated testing to assess risks and controls to identify internal control weaknesses during internal audit reviews and continuous auditing.</p>
<p>The audits cover Front Office Trading and Sales together with supporting control functions including Market and Credit Risk Management, Product Control / Middle Office, Technology and Compliance.
</p><p>Responsibilities include risk assessments, continuous monitoring, validating major control enhancements, reporting results to senior management, and contributing towards strategic and innovative changes to improve audit effectiveness.</p><br>
<p></p><p><b>Skill and Experience Requirements</b></p>
<ul><li>The primary skillset required is prior experience of data analysis. The candidate must be able to cite examples of applying data analysis skills and tools in a business or educational context.</li>
<li>Experience of trading systems, businesses, and the related operations, compliance, and finance areas in a broker-dealer or investment bank, or in an auditor / consultant role in a public accounting firm.</li>
<li>Experience of coding e.g. using Python and other languages, to provide insight into risks and/or controls such as IT general controls for e.g. change management, and analysis of data integrity to provide an audit opinion on the completeness, accuracy of system-based processing.</li>
<li>Knowledge of artificial intelligence tools and prompt engineering would be an advantage.
</li><li>Knowledge of databases: SQL, Elastic, Graph technologies, and Linux environments would be beneficial.</li>
<li>Knowledge of data visualization tools such as Power BI, Tableau, QlikView, etc. would be beneficial.</li>
<li>Knowledge of general auditing principles, including the ability to identify and document technology and business processes, and the design and operating effectiveness of related controls.</li>
<li>Confident manner and well-developed communication (both verbal and written), influencing, interpersonal and project management skills.</li><br>
</ul><p></p><p><b>Qualifications</b></p>
<ul><li>A bachelor&rsquo;s degree in Data Science, a Quantitative subject, Computer Science, Business, Finance, or related discipline.</li>
<li>Accounting or Audit professional qualifications (e.g., CISA) and / or securities licenses would be advantageous.</li>
<li>Knowledge of regulatory requirements in the US, Europe, and Asian markets would also be beneficial.</li><br>
</ul><p></p><div><b>Nomura Leadership Behaviors</b></div>
<div><b>Explore Insights &amp; Vision</b></div>
<ul><li>Identify the underlying causes of problems faced by you or your team and define a clear vision and direction for the future.</li>
</ul><div><b>Making Strategic Decisions</b></div>
<ul><li>Evaluate all the options for resolving the problems and effectively prioritize actions or recommendations.</li>
</ul><div><b>Inspire Entrepreneurship in People</b></div>
<ul><li>Inspire team members through effective communication of ideas and motivate them to actively enhance productivity.</li>
</ul><div><b>Elevate Organizational Capability</b></div>
<ul><li>Engage proactively in professional development and enhance team productivity through the promotion of knowledge sharing.</li>
</ul><div><b>Inclusion</b></div>
<ul><li>Foster a culture of inclusion and psychological safety in the workplace and cultivate a &quot;Risk Culture&quot; (Challenge, Escalate and Respect).</li><br>
</ul><div></div><ul><li>base pay offered may vary depending on multiple individualized factors, including market location, corporate and functional title and duties, job-related knowledge and advanced degrees, skills, and experience. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.</li></ul><br>
<div></div><div>If hired, employee will be in an &ldquo;at-will position&rdquo; and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors&rdquo;.</div><br>
<div></div><div><i>Nomura is an Equal Opportunity Employer</i></div><br>
</div></div></div></div><p></p><p><br>
<b>Nearest Major Market: </b>Manhattan
<br>
<b>Nearest Secondary Market: </b>New York City</p></div>

GM Technology Data Scientist Associate

The New York Times

<div><div><div><div><div><div><p><b>The </b><b>mission</b><b> of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It's why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It's why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it's why our business strategy centers on making journalism so good that it's worth paying for.</b></p>
</div>
</div></div></div></div><p><b>About the Role, Mission or Department Overview</b></p>
<p>
The New York Times is hiring a Machine Learning Scientist to join the New A.I. Products &amp; Platforms mission. We are a team building the next generation of reader-facing A.I. experiences for one of the world's most trusted news organizations.</p><br>
<p></p>
<p>
You will join a team of ML scientists developing embedding models and retrieval algorithms to power new A.I. experiences across our products. You will design and train embedding models for representation learning and fine-tune language models for custom use cases and content enrichment. Your work will allow teams across the company to build, deploy, and manage applications that use large language models (LLMs) to promote our journalism and our business. You will report to our Director, Machine Learning. This is a hybrid remote/in-office role.</p><br>
<p></p>
<p><b>
Responsibilities:</b></p>
<ul>
<li><p>You will design and train embedding models for representation learning, for example using transformer encoders and Two Tower architectures.</p>
</li>
<li><p>You will fine-tune and evaluate language models for custom use cases and content enrichment.</p>
</li>
<li><p>You will contribute to shared practices around evaluation, responsible A.I. use, and what &quot;good&quot; is inside an organization where judgment and independence are important</p>
</li>
<li><p>You will implement and deploy machine learning and AI research with robustness and reproducibility, with consideration of risks and trade-offs</p>
</li>
<li><p>You will adapt or develop ML and AI algorithms in cases when existing techniques are insufficient, while implementing simple approaches</p>
</li>
<li><p>You will communicate complex ideas in machine learning and AI while collaborating with all kinds of colleagues in engineering, analytics, product management, marketing, editorial, and executive leadership groups</p>
</li>
<li><p>Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.</p></li></ul><br>
<p>
</p><p><b>Basic Qualifications:</b></p>
<ul>
<li><p>PhD, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline</p>
</li>
<li><p>2+ years experience with open source machine learning or statistical analysis tools</p>
</li>
<li><p>2+ years coding experience in Python</p>
</li>
<li><p>2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis</p>
</li>
<li><p>1+ years of experience with deep learning architectures, fine-tuning, embeddings and Pytorch or Tensorflow</p></li></ul><br>
<p>
</p><p><b>Preferred Qualifications:</b></p>
<ul>
<li><p>1+ years of experience with information retrieval or search systems</p>
</li>
<li><p>1+ years of experience translating ambiguous business questions into machine learning problems</p>
</li>
<li><p>1+ years of experience building data products, either internal or consumer-facing</p>
</li>
</ul><p>REQ-020337</p><p></p><div><p><br>
For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.</p>
<p>
For roles outside of the U.S., information on benefits will be provided during the interview process.</p>
<p>
We're excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process.</p>
<p>
If you're an Engineering candidate, we'll let you know what specific GenAI tools you are permitted to use for your technical assessment.</p>
<p>
The New York Times Company is committed to being the world's best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.</p>
<p>
We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)'s Know Your Rights Poster is available here.</p>
<p>
The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.</p>
<p>
The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable &quot;Fair Chance&quot; laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.</p>
<p>
For information about The New York Times' privacy practices for job applicants click here.</p>
<p>
Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times.</p>
<p>
If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.</p></div></div><p></p>

Machine Learning Scientist, New AI Products and Platforms

T-Mobile

<div><p>At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That&rsquo;s how we&rsquo;re UNSTOPPABLE for our employees!</p><p></p>
At T-Mobile Advertising Solutions, we're building privacy-first advertising products powered by advanced machine learning, large-scale data processing, and cloud technologies. Our proprietary algorithms enable rich consumer insights, intelligent audience solutions, and measurable performance for advertisers while maintaining a strong commitment to consumer privacy.<br>
<br>
We are seeking a creative, and curious Senior Applied Scientist to join our team. In this role, you'll work at the intersection of machine learning, software engineering, and big data, building AI and ML systems that directly impact our customers and business. You'll collaborate with engineers, data scientists, product managers, and other stakeholders to solve complex problems and deliver innovative solutions at scale.<br>
<br>
We embrace Lean Development principles, iterative experimentation, continuous learning, and a strong build-measure-learn feedback culture. The work you do will directly shape the future of our products and technologies.<p></p><div><div><div><div><div><div><div><div><div><p><b>
Job Responsibilities</b>:</p><ul><li><p>
Lead the end-to-end development of machine learning and data products aligned to business objectives, from problem framing through deployment and monitoring.</p></li><li><p>
Build scalable data, training, and inference pipelines using distributed processing and cloud technologies.</p></li><li><p>
Apply statistical methods, experimentation, and validation frameworks to ensure solution quality and business impact.</p></li><li><p>
Write production-quality code and contribute to engineering best practices, including testing, CI/CD, and observability.</p></li><li><p>
Collaborate across engineering, product, and business teams while leading other engineers and data scientists.
</p></li></ul><p></p><p><b>Education and Work Experience</b>:</p><ul><li><p>
Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)</p></li><li><p>
Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)</p></li><li><p>
4-7 years experience building and deploying machine learning and deep learning solutions at scale; familiarity with MLOps and DevOps practices and tools. (Required)</p></li><li><p>
4-7 years Experience working within big data architecture, modern analytical data platforms, and large-scale data warehousing technologies (e.g. BigQuery, Snowflake, Redshift) (Required)</p></li><li><p>
4-7 years Experience working with large-scale distributed data systems and cloud platforms (e.g. SQL, Python, Scala, AWS) (Required)</p></li><li><p>
4-7 years Experience solving complex data, machine learning, or algorithmic challenges in production environment using modern engineering practices.(Required)</p></li></ul><p><b><br>
Knowledge, Skills and Abilities</b>:</p><ul><li><p>
Strong background in AI/ML, data structures, statistical modeling, optimization algorithms, big data, and design thinking.</p></li><li><p>
Advanced knowledge of cloud-based services (GCP, AWS)</p><p>
and Python, PySpark and related Python libraries (e.g. pandas, scikit-learn, scipy, numpy) for advanced data science tasks.</p></li><li><p>
Hands-on implementation and architectural familiarity with streaming data, relational and non-relational databases, and distributed processing technologies.</p></li><li><p>
Experience operating production machine learning and data systems in cloud and containerized environments.</p></li><li><p>
Experience in AdTech and GIS or geospatial data processing is a plus.</p></li></ul></div></div></div></div></div></div></div></div></div><p></p><ul><li><p>
At least 18 years of age</p></li><li><p>
Legally authorized to work in the United States</p></li></ul><p></p><p><b>
Travel</b>:<br>
Travel Required (Yes/No): No<br>
<br>
<b>DOT Regulated</b>:<br>
DOT Regulated Position (Yes/No): No<br>
Safety Sensitive Position (Yes/No): No</p><p></p>
Base Pay Range: $116,500 - $210,100<p></p>
Corporate Bonus Target: 15%<p></p><p>
The pay range above is the general base pay range for a successful candidate in the role. The successful candidate&rsquo;s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.</p><p></p>
At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee&rsquo;s eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, click here.<p></p><p>
At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&amp;D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance. We don't stop there - eligible employees can also receive mobile service &amp; home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T-Mobile&rsquo;s amazing benefits, check out <i>www.t-mobilebenefits.com</i><i>.</i></p><p></p><p>
Never stop growing!<br>
As part of the T-Mobile team, you know the Un-carrier doesn&rsquo;t have a corporate ladder&ndash;it&rsquo;s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it&rsquo;s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you&rsquo;re living our values while investing in your career growth&ndash;and we applaud it. You&rsquo;re unstoppable!<br>
<br>
T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated.<br>
<br>
Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing ApplicantAccommodation@t-mobile.com or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.</p></div>

Senior Applied Scientist

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.<br>
<br>
Key job responsibilities<br>
Participate in the Science hiring process as well as mentor other scientists - improving their skills, their knowledge of your solutions, and their ability to get things done.<br>
<br>
Identify and devise new video related solutions following a customer-obsessed scientific approach to address customer or business problems when the problem is ill-defined, needs to be framed, and new methodologies or paradigms need to be invented at the product level.
<br>
<br>
Articulate potential scientific challenges of ongoing or future customers&rsquo; needs or business problems, and present interventions to address them.<br>
<br>
Independently assess alternative video related technologies, driving evaluation and adoption of those that fit best
<br>
<br>
A day in the life<br>
As an Applied Scientist on the Sponsored Brands Video team, you will work with a team of talented and experienced engineers, scientists, and designers to help bring new products to market and ensure that our customers are delighted by what we create. The Sponsored Brands Video team is responsible for the design, development, and implementation of Sponsored Brands Video experiences worldwide.<br>
<br>
About the team<br>
The Sponsored Brands Video team within Sponsored Products and Brands creates relevant and engaging video experiences, connecting advertisers and shoppers. We are on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping delightful, &amp; personal.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually</div><p></p>

Applied Scientist III, Sponsored Products

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