data analyst

data engineer

data engineer ii

data scientist

senior data engineer

senior data scientist

Datavant

<div><div>Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world's health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient's request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health. 
 
By joining Datavant today, you're stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare.</div>
What We're Looking For

We are looking for a motivated Data Scientist to help Datavant revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

You'll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. You'll collaborate closely with cross-functional teams to:
<ul>
<li>Design and develop models to extract entities, detect intents, and understand document structure</li>
<li>Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs</li>
<li>Evaluate model performance where ground truth is partial, uncertain, or evolving</li>
<li>Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions</li>
</ul>
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If you're excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

What You Will Do
<ul>
<li>Play a key role in the success of our products by developing models for document understanding tasks.</li>
<li>Perform error analysis, data cleaning, and other related tasks to improve models.</li>
<li>Collaborate with your team by making recommendations for the development roadmap of a capability.</li>
<li>Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.</li>
<li>Understand product use-cases and define key performance metrics for models according to business requirements.</li>
<li>Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).</li>
</ul>
What You Need to Succeed
<ul>
<li>6+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.</li>
<li>Expertise with Python</li>
<li>Experience with the latest developments in language models (transformers, LLMs, etc.)</li>
<li>Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.</li>
<li>Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow</li>
<li>Industry experience shepherding ML/AI projects from ideation to delivery</li>
<li>Demonstrated ability to influence company KPIs with AI</li>
<li>Demonstrated ability to navigate ambiguity</li>
</ul>
What Helps You Stand Out
<ul>
<li>Experience with document layout analysis (using vision or multi-modal approaches).</li>
<li>Experience with Spark/PySpark</li>
<li>Experience with Databricks</li>
<li>Experience in the healthcare industry</li>
</ul>
After 3 Months, You Will&hellip;
<ul>
<li>Have a strong grasp of technologies upon which our platform is built.</li>
<li>Be fully integrated into ongoing model development efforts with your team.</li>
</ul>
After 1 Year, You Will&hellip;
<ul>
<li>Be independent in reading literature and doing research to develop models for new and existing products.</li>
<li>Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.</li>
<li>Be a subject matter expert on Datavant's models and a source from which other teams can seek information and recommendations.</li>
</ul>
#LI-BC1<div>
To ensure the safety of patients and staff, many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot, Tdap, COVID-19, etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working, exemptions may be available on the basis of disability, medical contraindications to the vaccine or any of its components, pregnancy or pregnancy-related medical conditions, and/or religion.
 
 
This job is not eligible for employment sponsorship. 
 
Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. To learn more about our commitment, please review our EEO Commitment Statement here. Know Your Rights, explore the resources available through the EEOC for more information regarding your legal rights and protections. In addition, Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay. 
 
At the end of this application, you will find a set of voluntary demographic questions. If you choose to respond, your answers will be anonymous and will help us identify areas for improvement in our recruitment process. (We can only see aggregate responses, not individual ones. In fact, we aren't even able to see whether you've responded.) Responding is entirely optional and will not affect your application or hiring process in any way. 
 
Datavant is committed to working with and providing reasonable accommodations to individuals with physical and mental disabilities. If you need an accommodation while seeking employment, please request it here, by selecting the 'Interview Accommodation Request' category. You will need your requisition ID when submitting your request, you can find instructions for locating it here. Requests for reasonable accommodations will be reviewed on a case-by-case basis. 
<div>
<div><div><div>For more information about how we collect and use your data, please review our Privacy Policy.</div></div></div></div></div></div>

Senior Data Scientist, NLP

Louis Vuitton

<div>
 
 About The Job
 
 
 
 Louis Vuitton Americas is seeking a Senior Data Scientist &ndash; Analytics and AI Data to join our Digital team based in New York City. This individual will act as a hybrid data scientist, MLOps engineer, BI SME, business analyst, and data engineer, while owning the roadmap of analytics and AI solutions that can be industrialized and scaled by central teams. You will sit at the intersection of local business needs and global data/AI strategy, ensuring solutions are impactful, scalable, and aligned with enterprise priorities.
 
 
 Job responsibilities
 
 
 <ul>
 <li>
 Product Strategy &amp; Cross-Functional Roadmap:
 
 </li>
 <ul>
 <li>
 Lead the comprehensive analytics and AI roadmap, guiding it from opportunity identification and prioritization through delivery and transition to central teams.
 </li>
 <li>
 Collaborate with diverse functional stakeholders (e-commerce, retail, CRM, supply chain, finance, etc.) to identify use cases, define problem statements, and translate these into clear data product requirements.
 </li>
 <li>
 Establish success metrics, measure value realization, and continuously refine the roadmap based on impact and feedback.
 
 </li>
 </ul>
 <li>
 Data Science &amp; Advanced Analytics:
 
 </li>
 <ul>
 <li>
 Design and lead predictive models and analytical solutions utilizing Python and SQL.
 </li>
 <li>
 Conduct thorough exploratory data analysis, feature engineering, model training, validation, and comprehensive documentation.
 </li>
 <li>
 Develop reusable analytical assets (scores, segments, KPIs) for broad application across various markets and functions.
 
 </li>
 </ul>
 <li>
 MLOps &amp; Data Engineering:
 
 </li>
 <ul>
 <li>
 Collaborate with MLOps and Data Engineering teams to develop, orchestrate, and maintain robust data and machine learning pipelines, leveraging tools such as Dataiku and Google BigQuery.
 </li>
 <li>
 Implement best practices for testing, version control, monitoring, and observability to ensure the creation of reliable, production-grade solutions.
 </li>
 <li>
 Partner with central data engineering and platform teams to align initiatives with enterprise standards and promote scalability.
 </li>
 <li>
 Work alongside business, local, and central Data Engineering teams to facilitate data integration and validation, effectively addressing diverse business challenges.
 
 </li>
 </ul>
 <li>
 BI, Insights &amp; Business Analysis:
 
 </li>
 <ul>
 <li>
 Act as a Business Intelligence Subject Matter Expert, contributing to the definition of semantic layers, Key Performance Indicators (KPIs), and data models that enable self-service analytics.
 </li>
 <li>
 Guide or develop insightful dashboards and reports using tools like Power BI, Tableau, or Looker, ensuring their actionability and broad adoption across the organization.
 </li>
 <li>
 Perform business analysis, meticulously gathering requirements, mapping processes, and transforming analytical findings into clear recommendations and compelling narratives for various stakeholders.
 
 </li>
 </ul>
 <li>
 Collaboration with Central / Global Teams:
 
 </li>
 <ul>
 <li>
 Prepare and package local or cross-functional solutions, including code, design specifications, documentation, and KPIs, for industrialization and ongoing maintenance by central teams.
 </li>
 <li>
 Contribute to the continuous evolution of global data and AI standards, reference architectures, and best practices.
 </li>
 <li>
 Represent cross-functional analytics and AI needs in global forums, effectively highlighting dependencies, potential risks, and opportunities for scaling solutions.
 
 
 </li>
 </ul>
 </ul>
 Profile
 
 
 We are excited to speak to skilled and experienced data professional with 3+ years of hands-on experience in data science, analytics, or data engineering, demonstrating end-to-end ownership of data products. The ideal candidate will possess strong proficiency in Python (pandas, NumPy, scikit-learn), advanced SQL skills, and experience with cloud data warehouses such as Google BigQuery. Practical experience with enterprise data processing platforms like Dataiku is also essential. Candidates should have demonstrated expertise in at least three of the following areas: data science/machine learning, BI/reporting and metric design, business analysis/stakeholder management, data engineering/data processing, or Gen AI/Agentic AI product deployment. Strong communication and storytelling abilities are crucial for fostering collaboration between business and technical teams.
 
 
 Preferred qualifications include experience in retail, luxury, fashion, or consumer environments, familiarity with experimentation (A/B testing), customer analytics (segmentation, propensity, churn, LTV), or marketing attribution. Exposure to Generative AI/LLMs and their application to customer experience and productivity, along with experience in a hub-and-spoke operating model, are also highly valued. Core competencies for this role include transversal product thinking, technical breadth spanning data science, MLOps, BI, data analysis, and data engineering, the ability to lead initiatives effectively across functions and geographies, and a strong outcome orientation focused on measurable business value and long-term maintainability.
 
 
 The appointed candidate will be offered a base salary within the range USD $140,000 - $160,000, a comprehensive benefits package including: medical, dental, vision, short and long-term disability, various paid time off programs, employee discount/perks and two retirement plans both with employer contributions.
 
 
 <ul>
 <li>
 Please note that restrictions may apply to part-time employees
 
 
 </li>
 </ul>
 
 The position requires 4 days per week on site in the Louis Vuitton Corporate Office, located in the heart of Midtown, Manhattan.
 
 
 
 Additional information
 
 
 Louis Vuitton is a company that respects the uniqueness of each employee and offers everyone the means to find their place and prosper. We promote initiatives aimed at supporting professional equality for everyone. We strive to go above and beyond purely symbolic measures by building a culture passionate about meaningful strategies aimed at crafting an inclusive workforce.
 
 
 In addition to a generous benefits package, unparalleled career development opportunities, both locally &amp; globally, as an employee at Louis Vuitton, you can expect to be provided with industry leading training which will offer you an in-depth insight into the luxury and retail environment.
 
 
 Reference LVM32143
</div>

Senior Data Scientist – Analytics and AI Data

Doppel

<div>
 
 Why Join Doppel
 
 
 
 Doppel is built to outsmart one of the great threats AI presents: mass-manufactured social engineering. Countless scams, deepfakes, and other social engineering attacks are surging across every digital channel: websites, social media, ads, encrypted messaging apps, mobile, and more. Our mission is simple but bold: make the internet a safer place by outsmarting the world&rsquo;s fastest-evolving digital threats.
 
 
 Backed by top-tier investors and trusted by some of the world&rsquo;s most recognized brands, Doppel is growing fast. If you&rsquo;re driven to solve real-world problems with bold technology, we&rsquo;d love to meet you.
 
 
 
 What We're Building
 
 
 
 We're building the AI-native social engineering defense platform.
 
 
 This means we're designing scalable systems that monitor billions of domains, social media accounts, apps, dark web forums, etc., and leverage AI agents to identify and neutralize digital threats.
 
 
 
 What We're Looking For
 
 
 
 We're hiring for a senior data scientist specifically focused on product analytics. We&rsquo;re looking for a customer-obsessed data scientist who wants to have outsized impact and ownership. This role will play a significant role in shaping our roadmap. You&rsquo;ll get the opportunity to join a rapidly growing company that&rsquo;s making the Internet a safer place every day. We're in-person in SF/NY 3 days a week.
 
 
 
 We&rsquo;re Looking For Someone To
 
 
 
 <ul>
 <li>
 Define the right product and customer metrics to measure success and identify new areas of opportunity.
 </li>
 <li>
 Build scalable, self-serve dashboards to help cross-functional teams make data-driven decisions.
 </li>
 <li>
 Create analytical models to support our product, engineering, and operations teams.
 </li>
 <li>
 Develop forecasting models to estimate operational capacity over time, especially as we leverage AI to combat online threats.
 </li>
 <li>
 Communicate insights clearly to technical and non-technical teams.
 
 
 </li>
 </ul>
 
 Our Ideal Candidate Has
 
 
 
 <ul>
 <li>
 4+ years of experience in data analytics, data science, or a related field.
 </li>
 <li>
 Fluency in BigQuery/SQL and familiarity with data visualization tools like Looker Studio.
 </li>
 <li>
 Strong foundational understanding of statistical methods, forecasting, and/or experimentation.
 </li>
 <li>
 Experience working cross-functionally and collaborating with product, engineering, and non-technical partners.
 
 
 </li>
 </ul>
 While it&rsquo;s not required, it&rsquo;s a bonus to be familiar with a language like R or Python, especially if you have experience writing Jupyter notebooks.
 
 
 If you&rsquo;re excited about the role but your past experience doesn&rsquo;t align perfectly with the above, we encourage you to apply anyway.
 
 
 
 What We Offer
 
 
 
 🚀 A mission-driven culture with low ego, high ownership, deep customer obsession, and exceptional talent density
 
 
 🍽️ Free lunch and dinner in the office
 
 
 🌴 Flexible PTO
 
 
 ✈️ Quarterly team offsites
 
 
 Join Doppel
 
 
 Doppel is the first platform built to dismantle digital deception at scale. We scan over 150 billion entities daily and deploy continuously adaptive AI SOC agents, paired with expert human analysts, to uncover and disrupt the infrastructure behind phishing, impersonation, and online fraud before attacks can spread. Our Threat Grid turns every customer signal into shared intelligence, making each disruption smarter, faster, and more effective.
 
 
 We&rsquo;re not just another cybersecurity company. We&rsquo;re defining the future of social engineering defense, where trust is protected, and deception becomes unprofitable. Backed by top-tier investors and trusted by some of the world&rsquo;s most recognized brands, Doppel is growing fast. If you&rsquo;re driven to solve real-world problems with bold technology, we&rsquo;d love to meet you.
</div>

Data Scientist

Stott and May

<div>
 
 
 Data Scientist / Data Engineer (Ecommerce) Contract Opportunity
 
 
 
 
 
 
 
 Work:
 
 
 
 We&rsquo;re supporting an ecommerce client looking for a hybrid
 
 Data Scientist / Data Engineer
 
 contractor to help scale data products and drive insights across customer, product, and digital performance data.
 
 
 
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Build and maintain data pipelines supporting analytics and machine learning use cases
 </li>
 <li>
 Develop models and analyses around customer behavior, recommendations, forecasting, and conversion optimization
 </li>
 <li>
 Work with large-scale ecommerce data (clickstream, transactions, inventory, marketing)
 </li>
 <li>
 Design and optimize datasets for reporting, experimentation, and predictive modeling
 </li>
 <li>
 Partner with analytics, product, and engineering teams to productionize solutions
 </li>
 <li>
 Support data quality, performance tuning, and scalable data architecture
 </li>
 </ul>
 
 
 Requirements:
 
 
 <ul>
 <li>
 Strong Python and SQL skills
 </li>
 <li>
 Experience in both data engineering and data science / ML workflows
 </li>
 <li>
 Background building pipelines with tools like Airflow, Spark, dbt, or similar
 </li>
 <li>
 Experience with cloud platforms such as AWS, GCP, or Azure
 </li>
 <li>
 Exposure to recommendation systems, forecasting, customer analytics, or experimentation (A/B testing) preferred
 </li>
 <li>
 Ecommerce, retail, or marketplace data experience strongly preferred
 </li>
 </ul>
 
 
 Details:
 
 
 <ul>
 <li>
 Fully remote
 </li>
 <li>
 40 hours/week (full-time
 
 contract
 
 )
 </li>
 <li>
 Initial 6-month
 
 contract
 
 with likely extension
 </li>
 <li>
 W2 or personal LLC only (
 
 no C2C
 
 )
 </li>
 <li>
 Rates competitive and dependent on experience (target $80&ndash;$110/hr)
 </li>
 </ul>
 
 
</div>

CVS Health

<div>We&rsquo;re building a world of health around every individual &mdash; shaping a more connected, convenient and compassionate health experience. At CVS Health&reg;, you&rsquo;ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger &ndash; helping to simplify health care one person, one family and one community at a time.
The Retail Pharmacy Operations Analytics team is looking for a Senior Decision Scientist to support RX and immunization growth initiatives.<ul><li>
Develop and present meaningful and insights-driven materials on analytical results with recommendations and go forward planning to guide a variety of audiences including internal stakeholders and senior leadership.</li><li>
Drive self-service capabilities with the business, train business teams on new technical capabilities and how to consume the data effectively, prove out new tools/capabilities quickly through POCs and provide readouts to the management teams.</li><li>
Build relationships across the enterprise, working with analytics and data teams for insights and best practice sharing.</li><li>
Partner with functional and business stakeholders to understand strategic business analytics requirements</li><li>
Provide guidance in driving solutions while delivering successful end results</li><li>
Develop strategies aimed to improve business reporting and planning processes utilizing continuous improvement.</li><li>
Use data visualization techniques to effectively communicate analytical results and support business decisions</li><li>
Work with a sense of urgency, possess strong critical thinking and analytical skills, and have passion for developing high-performing analytics solutions</li></ul>
Required Qualifications :<ul><li>
3+ years of relevant analytic experience</li><li>
Experience programming using R or Python</li><li>
Experience in SAS or SQL</li></ul>
Preferred Qualifications :<ul><li>
Demonstrates strong ability to communicate technical concepts and implications to business partners.</li><li>
Anticipates and prevents problems and roadblocks before they occur.</li><li>
Strong knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources.</li><li>
Demonstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and in-depth specialization in some areas.</li><li>
Hands-on experience with cloud computing (Google Cloud, AWS, etc.) and tools/processes for version control (i.e. git, GitHub) preferred.</li><li>
Experience with data visualization tools (Tableau, Plotly, etc).</li></ul>
Education :<ul><li>
Bachelor's degree or equivalent work experience in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or related discipline.</li><li>
Master's degree preferred</li></ul>
Anticipated Weekly Hours
40
Time Type
Full time
Pay Range
The typical pay range for this role is:
$111,240.00 - $222,480.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. 
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. 
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. 
Additional details about available benefits are provided during the application process and on Benefits Moments. 
We anticipate the application window for this opening will close on: 05/31/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.</div>

Senior Decision Scientist - Retail Pharmacy Operations

Impact.Com

<div>About impact.com 
impact.com is the world's leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L'Or&eacute;al, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale &mdash; sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization &mdash; making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer &mdash; and to be genuinely excited about both.

What You'll Do:

Yield Optimization &amp; Pricing Models
<ul>
<li>Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.</li>
<li>Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.</li>
<li>Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.</li>
<li>Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.</li>
</ul>
Inventory Allocation &amp; Supply Optimization
<ul>
<li>Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.</li>
<li>Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.</li>
<li>Identify and address inefficiencies in inventory utilization &mdash; including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.</li>
</ul>
Data Architecture &amp; Feature Engineering
<ul>
<li>Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.</li>
<li>Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance &mdash; at the scale of programmatic data volumes.</li>
<li>Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.</li>
</ul>
Real-Time Inference &amp; Production ML
<ul>
<li>Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.</li>
<li>Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.</li>
<li>Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.</li>
<li>Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.</li>
</ul>
Experimentation &amp; Performance Measurement
<ul>
<li>Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.</li>
<li>Build evaluation frameworks that go beyond offline metrics &mdash; validating model behavior in live auction environments where feedback signals are delayed or noisy.</li>
<li>Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.</li>
</ul>
Self-Learning Systems &amp; Feedback Loops
<ul>
<li>Research and implement adaptive, self-learning components within the programmatic stack &mdash; including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.</li>
<li>Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.</li>
<li>Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.</li>
</ul>
Cross-Functional Collaboration
<ul>
<li>Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.</li>
<li>Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.</li>
<li>Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.</li>
</ul>
What You Bring:

Required
<ul>
<li>Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).</li>
<li>Programmatic &amp; marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.</li>
<li>Production ML engineering: Proven ability to take models from prototype to production independently &mdash; including real-time inference, monitoring, retraining pipelines, and SLO ownership.</li>
<li>Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.</li>
<li>Technical skills:</li>
<li><ul><li>Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).</li>
<li>Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).</li>
<li>Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.</li>
<li>Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.</li>
</ul></li><li>Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).</li>
<li>Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.</li>
<li>Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.</li>
</ul>
Preferred / Nice to Have
<ul>
<li>Direct experience with SSP, DSP, or exchange-side yield optimization &mdash; particularly floor price optimization, bid landscape modeling, or deal matching algorithms.</li>
<li>Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.</li>
<li>Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.</li>
<li>Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.</li>
<li>Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).</li>
<li>Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.</li>
<li>Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.</li>
<li>Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.</li>
</ul>
What Sets You Apart
<ul>
<li>Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist &mdash; you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.</li>
<li>Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.</li>
<li>Feedback loop thinking. You don't just deploy models &mdash; you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.</li>
<li>Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.</li>
<li>Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.</li>
<li>Collaborative depth. You build genuine technical trust with engineering and product partners &mdash; not just by having good ideas, but by following through, communicating clearly, and making the integration easy.</li>
</ul>
Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.
<ul><li>This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.</li></ul>

Benefits and Perks:

At impact.com, we believe that when you're happy and fulfilled, you do your best work. That's why we've built a benefits package that supports your well-being, growth, and work-life balance.
<ul>
<li>Medical, Dental, and Vision insurance</li>
<li>Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled</li>
<li>Flexible spending accounts and 401(k)</li>
<li>Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.</li>
<li>Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.</li>
<li>A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.</li>
<li>Investing in Your Growth: We're committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.</li>
<li>Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.</li>
<li>Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses.</li>
</ul>
impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors. 


#LI_NewYork_NewYork</div>

Sr. Data Scientist, Programmatic Algorithms

JPMorganChase

<div>JOB DESCRIPTION 
Help shape how we understand the economy through data. In this role, you&rsquo;ll work with macroeconomic and financial datasets to uncover emerging trends, explain what&rsquo;s driving them, and communicate insights clearly. You&rsquo;ll have the opportunity to grow your analytics toolkit while partnering with experts across data science and economics. Join a team that values curiosity, rigor, and impact.
Job Summary
As a Data Scientist within the Center for Economic Intelligence, you will help drive analytics workflow and development by deploying modern approaches to data design, modeling, analysis, and visualization of macroeconomic and financial data. You&rsquo;ll join an organization focused on developing a holistic internal and external view of the financial well-being of consumers and businesses using internal and third-party data. You&rsquo;ll collaborate with Data Scientists, Economists, and Econometricians to identify emerging trends and the economic relationships behind them. You will communicate findings with clear narratives and strong data support to inform decision-making.
During a period of heightened macroeconomic uncertainty, identifying early signals in income, spending, savings, and credit is especially important. You&rsquo;ll contribute to a team culture that prizes attention to detail, thoughtful debate, and delivering results at pace. You&rsquo;ll also help translate complex analyses into presentations for senior stakeholders, sponsors, and colleagues.
Job Responsibilities<ul><li>
Recognize and communicate meaningful trends and patterns related to consumer and business health</li><li>
Collaborate with Data Scientists, Economists, and Econometricians to explore trends in income, spending, savings, and credit</li><li>
Apply advanced analytical techniques to develop detailed explanations of broader economic trends</li><li>
Identify and validate data sources while assessing data quality and fitness for purpose</li><li>
Translate analytical results into clear, concise insights backed by strong data support</li><li>
Contribute critical thinking and attention to detail in a fast-paced, results-oriented environment</li><li>
Develop presentations that summarize key messages for senior management, sponsors, and colleagues</li><li>
Promote continuous learning by bringing new ideas and perspectives that strengthen team thinking</li></ul>
Required Qualifications, Capabilities, and Skills<ul><li>
Four years of experience in a business strategy and analytics role</li><li>
Bachelor&rsquo;s degree in a related field</li><li>
Substantial SQL experience</li><li>
Strong experience with at least one of the following: Python or R</li><li>
Strong written and verbal communication, with the ability to frame messages for different audiences</li><li>
Strong critical and analytical thinking skills</li><li>
Ability to work independently and manage shifting priorities and projects</li><li>
Strong attention to detail while retaining a big-picture perspective</li><li>
Strong experience using analytical tools and techniques to extract meaningful insights from data</li><li>
Basic knowledge of statistics, econometrics, and machine learning modeling (including supervised and unsupervised learning techniques)</li><li>
Familiarity with macroeconomic trends and indicators</li><li>
Familiarity using Tableau</li></ul>
ABOUT US 
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans 
 
 
ABOUT THE TEAM 
<div>
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div><div> 
 
</div><div>The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.</div></div>

Data Scientist, Sr Associate - Center for Economic Intelligence

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