data analyst

data engineer

data scientist

associate data analyst

data & cloud engineer

senior data scientist

Pfizer

<div><div>ROLE SUMMARY</div><div>
Plan and perform care gap advanced analytics and segment HCPs and KOLs using real world data sources as input.</div><div></div><div>
ROLE RESPONSIBILITIES</div><div>
Strategic support and communications</div><ul><li><div>
Support Care Gaps &amp; Segmentation Team Leader in strategic and tactical planning with regards to medical analyses.</div></li><li><div>
Collaborate with Care Gaps &amp; Segmentation Team Leader to communicate generated insights</div></li><li><div>
Provide mentorship &amp; coaching to Data Scientists &amp; Data Engineering.</div></li><li><div>
Leverage cross-team collaboration and asset-specific experience to develop and disseminate analytical best-practices in conducing care gap analyses and HCP segmentation.</div></li><li><div>
Proactively identify future opportunities, such as data inputs, innovative analytical tools, and capability-building initiatives to enhance the impact and adoption of care gap and segmentation solutions.</div></li></ul><div></div><div>
Planning and conducting medical analyses</div><ul><li><div>
Prepare and maintain datasets for on-going high-complexity analytical needs, in collaboration with data engineers, including flagging data issues &amp; advising on required solutions.</div></li><li><div>
Own the end-to-end process of integrated care gaps analyses, including strategic planning, identifying data input required (e.g., claims data for unmet need analysis), and effective visualization / insight generation for users.</div></li><li><div>
Plan, generate and perform asset-specific care gap analyses to guide Medical Affairs activities using advanced techniques such as predictive models, machine learning, probabilistic causal models, and unsupervised algorithms.</div></li><li><div>
Create asset-specific HCP segments, maps, and prioritizations, across multiple dimensions including care gaps, to guide channel mix/activation, content creation, and MSL activity in Anchor countries.</div></li></ul><div></div><div>
BASIC QUALIFICATIONS</div><ul><li><div>
Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.</div></li><li><div>
Degree in Data Sciences, or Computer Sciences, Statistics, Clinical Informatics or similar, with advanced qualification in Data Science.</div></li><li><div>
Relevant certification &amp;/or work experience in data engineering.</div></li><li><div>
Experience (8+ years with Bachelors; 7+ with Masters; 5+ with PHD) in data sciences, notably in the healthcare sector.</div></li><li><div>
Demonstrated ability to independently lead projects &amp; support professional growth of colleagues.</div></li><li><div>
Demonstrated effectiveness working in cross-functional business environment.</div></li><li><div>
Proven influencing skills.</div></li><li><div>
Strong interpersonal skills to quickly build rapport and credibility with Pfizer leaders and key external stakeholders.</div></li><li><div>
Ability to partner cross culturally/regionally.</div></li><li><div>
Effective English verbal and written communication with flexibility to be clear, consistent, compliant, and appropriate for a variety of settings including scientific/technical, promotional, patient/consumer, regulatory, and media.</div></li><li><div>
In depth understanding of the business of pharmaceutical medicine including clinical trial design, GCP and data interpretation, drug development, regulatory and promotional rules/guidance, legal and compliance, issue management and business development opportunity evaluations.</div></li></ul><div></div><div>
Technical:</div><ul><li><div>
Anticipates Customer and Market Needs &ndash; Knows the industry; knowledgeable in current and possible future trends, knows the competition; is aware of how strategies and tactics work in the marketplace. Is dedicated to meeting the expectations and requirements of internal and external customers; always focused on patient safety first, establishes and maintains effective relationships with customers and gains their trust and respect.</div></li><li><div>
Acts Decisively &ndash; Makes timely and effective decisions by applying business and financial acumen. Acts with urgency and removes barriers that hinder productivity. Can be counted on to exceed goals successfully; is very bottom-line oriented; steadfastly pushes self and others for results.</div></li><li><div>
Builds Change-Agile Organizations &ndash; Develops teams that are facile at initiating and responding to change. Aligns teams and processes to support sustainable change.</div></li><li><div>
Designs and leads teams that are flexible and adaptive.</div></li><li><div>
Strategic and Innovating Thinking &ndash; Demonstrates insightful thinking by developing creative approaches to business models and strategies and creates an environment to encourage others to do the same.</div></li><li><div>
Grows Leaders &ndash; Actively coaches and develops talent. Builds leadership bench strength for Pfizer. Provides opportunities and experiences to develop skills, competencies, and business knowledge.</div></li><li><div>
Is a role model of Pfizer&rsquo;s values and behaviors.</div></li><li><div>
Demonstrate ability to:</div><ul><li><div>
Drive transformational change</div></li><li><div>
Lead teams and engage diverse stakeholders</div></li><li><div>
Understand the applications of technology to the Life Science sector</div></li></ul></li></ul><div></div><div>
Other Job Details</div><ul><li><div>
Last day to apply: April 2, 2026</div></li><li><div>
Additional Location Information: Canada; Quebec; Montreal, Canada; Remote, California; La Jolla, Connecticut; Groton, Florida; Tampa, Massachusetts; Cambridge, Pennsylvania; Collegeville, United States; Remote</div></li><li><div>
Eligible for Relocation Package: No</div></li></ul><div>
#LI-PFE</div><br>
The annual base salary for this position ranges from $162,900.00 to $271,500.00.* In addition, this position is eligible for participation in Pfizer&rsquo;s Global Performance Plan with a bonus target of 20.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life&rsquo;s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site &ndash; U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.
* The annual base salary for this position in Tampa, FL ranges from $146,600.00 to $244,400.00.<div><br>
Relocation assistance may be available based on business needs and/or eligibility.</div><div><br>
Candidates must be authorized to be employed in the U.S. by any employer.</div><div>
U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.</div><div><div><div><div><div><div><div><div><div><br>
Sunshine Act</div><div>
Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider&rsquo;s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.</div></div></div></div></div></div></div></div></div><div><div><div><div><div><div><div><div><div><br>
EEO &amp; Employment Eligibility</div><div>
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.</div><div></div><div>
Pfizer endeavors to make <div>www.pfizer.com/careers</div> accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email <div>disabilityrecruitment@pfizer.com</div>. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.</div></div></div></div></div></div></div></div></div><br>
Marketing and Market Research</div>

Senior Data Scientist Medical Analytics, Care Gaps & Customer Segmentation Team

Stott and May

<div>
 <p>
  We&rsquo;re working with a digital client looking to bring on an experienced
  <strong>
   Data Scientist
  </strong>
  to support applied analytics and ML initiatives across an established cloud data platform.
 </p>
 <p>
  <br/>
 </p>
 <p>
  You&rsquo;ll join an existing delivery team as a senior individual contributor, working hands on across modeling, experimentation, and production deployment, with visibility across multiple business domains.
 </p>
 <p>
  <br/>
 </p>
 <p>
  This suits someone practical and commercially minded, comfortable taking models from idea through to production.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Six month initial contract with strong likelihood of rolling extensions.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Competitive hourly rates depending on experience, 40 hrs/week.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Engagement via W2 or personal LLC only.
  <strong>
   No third parties.
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  Fully remote, aligned to EST.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What you&rsquo;ll be doing
  </strong>
 </p>
 <p>
  &bull; Building predictive and statistical models for real business use cases
 </p>
 <p>
  &bull; Working with large structured and semi structured datasets
 </p>
 <p>
  &bull; Partnering with data engineering to productionize models
 </p>
 <p>
  &bull; Designing experiments and validating model performance
 </p>
 <p>
  &bull; Translating business problems into analytical solutions
 </p>
 <p>
  &bull; Supporting model monitoring and continuous improvement
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What we&rsquo;re looking for
  </strong>
 </p>
 <p>
  &bull; Strong experience as a Data Scientist in production environments
 </p>
 <p>
  &bull; Solid Python and SQL
 </p>
 <p>
  &bull; Experience with ML frameworks (scikit-learn, XGBoost, PyTorch, etc.)
 </p>
 <p>
  &bull; Strong statistics and modeling fundamentals
 </p>
 <p>
  &bull; Comfortable working with messy, real-world data
 </p>
 <p>
  &bull; Experience in agile, delivery-focused teams
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Nice to have
  </strong>
 </p>
 <p>
  &bull; Cloud experience (AWS / Azure / GCP)
 </p>
 <p>
  &bull; Feature engineering and model deployment exposure
 </p>
 <p>
  &bull; Experience supporting product or growth teams
 </p>
 <p>
  &bull; Basic MLOps familiarity
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Why this role
  </strong>
 </p>
 <p>
  &bull; Applied data science, not research
 </p>
 <p>
  &bull; Real business impact
 </p>
 <p>
  &bull; Flexible engagement model, extensions likely
 </p>
 <p>
  &bull; Opportunity to work with experienced data teams
 </p>
</div>


Data Scientist

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>
  Salary Range:
 </strong>
 US$ 140,000-190,000/year
 <br/>
 <br/>
 <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/>
 <br/>
 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.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <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
 <br/>
 <br/>
 <ul>
  <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <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
  <br/>
  <br/>
 </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)
  <br/>
  <br/>
 </strong>
 Candidates with at least one relevant certification are especially encouraged to apply:
 <br/>
 <br/>
 <ul>
  <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
  <br/>
  <br/>
 </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
 <br/>
 <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>
 Powered by JazzHR
 <br/>
 <br/>
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</div>


Career Renew

<div>
 <span>
  &hairsp;Career Renew is recruiting for one of its clients a Product Data Scientist - Crypto - this is a fully onsite role for London or New York based candidates. Salary range: 250-300K USD yearly.
 </span>
 <br/>
 &nbsp;
 <br/>
 <br/>
 <br/>
 <br/>
 <p>
  <span>
   <strong>
    About the Role
   </strong>
  </span>
 </p>
 <br/>
 <p>
  <span>
   We're seeking an experienced, versatile Product Data Scientist who thrives in a fast-paced environment. In this role,&nbsp;
  </span>
  <span>
   you'll have the freedom to identify opportunities, design and implement solutions, and measure their impact
  </span>
  <span>
   across our product. You'll collaborate with cross-functional teams while maintaining ownership of your
  </span>
  <span>
   projects from conception to completion.
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   <strong>
    What You'll Do
   </strong>
  </span>
 </p>
 <br/>
 <ul>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Design, run, and analyze A/B tests to optimize our consumer product experience
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Proactively identify problems and opportunities through data analysis
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Build and maintain dashboards to track key metrics and visualize insights
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Develop models to understand user behavior and predict outcomes
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Collaborate with product and engineering teams to implement data-driven solutions
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Drive projects independently from problem identification through solution implementation
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Communicate complex findings clearly to technical and non-technical stakeholders
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Help establish data best practices and methodologies
    </span>
   </p>
   <br/>
   <p>
    &nbsp;
   </p>
   <br/>
  </li>
  <br/>
 </ul>
 <br/>
 <p>
  <span>
   <strong>
    Requirements
   </strong>
  </span>
 </p>
 <br/>
 <ul>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     2-3 years of data science experience at a startup, scale-up, or FAANG/equivalent company
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Proficiency with Python/R and SQL/BigQuery
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Strong experience designing, running, and analyzing A/B tests on consumer products
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Demonstrated ability to work autonomously, managing entire projects from ideation to implementation
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Experience translating data insights into actionable recommendations
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Excellent communication skills, with the ability to present complex findings clearly
    </span>
   </p>
   <br/>
  </li>
  <br/>
 </ul>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   <strong>
    Preferred Qualifications
   </strong>
  </span>
 </p>
 <br/>
 <ul>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Experience with cryptocurrency and blockchain data
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Strong data visualization skills (especially with Grafana)
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Experience working with event tracking data (especially FullStory)
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Advanced knowledge of statistical methods and causal inference
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Experience building and maintaining data pipelines (especially with Dataform)
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Familiarity with Machine Learning methods and applications
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Experience in consumer tech products or fintech
    </span>
   </p>
   <br/>
  </li>
  <br/>
 </ul>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   <strong>
    What We're Looking For
   </strong>
  </span>
 </p>
 <br/>
 <p>
  <span>
   We value generalists over specialists. The ideal candidate has breadth across the data science field rather
  </span>
  <span>
   than deep expertise in just one area. You should be proactive, self-motivated, and comfortable taking initiative
  </span>
  <span>
   to find problems worth solving. You'll thrive in our environment if you enjoy autonomy and are excited about
  </span>
  <span>
   having end-to-end ownership of your work.
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   <strong>
    Benefits
   </strong>
  </span>
 </p>
 <br/>
 <ul>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Competitive salary and equity package
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Flexible work arrangements
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Comprehensive health benefits
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Professional development budget
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Collaborative, fast-paced environment
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     Opportunity to shape the future of [industry/product]
    </span>
   </p>
   <br/>
  </li>
  <br/>
  <li>
   <br/>
   <p>
    <span>
     We're building a diverse team and encourage applications from candidates of all backgrounds
    </span>
   </p>
   <br/>
  </li>
  <br/>
 </ul>
 <br/>
 <br/>
 <br/>
 <br/>
 <span>
  Compensation &amp; Package
 </span>
 <br/>
 <br/>
 <p>
  <span>
   Base Salary + Equity/Tokens
  </span>
 </p>
</div>


Product Data Scientist - Crypto

Data Scientist, Product Analytics

Lyft

<div>
 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
 <br/>
 <br/>
 Data Science is central to Lyft's products and decision-making. As a Data Scientist on the cross-functional team, you will work in a dynamic environment, tackling a variety of problems from shaping critical business decisions to building algorithms that power our products. We seek passionate, driven Data Scientists to address some of the most interesting and impactful problems in ridesharing.
 <br/>
 <br/>
 As a Data Scientist specializing in Algorithms, you will develop mathematical models for the platform's core services, addressing diverse problems in optimization, prediction, machine learning, and inference. On the Fulfillment team, you will collaborate with cross-functional teammates and stakeholders to enhance algorithms for matching rideshare supply and demand in real time and develop product offerings to improve the experiences of Lyft Riders and Drivers.
 <br/>
 <br/>
 <strong>
  Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team&rsquo;s systems and products
  </li>
  <li>
   Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
  </li>
  <li>
   Perform exploratory data analysis to gain a deeper understanding of the problem
  </li>
  <li>
   Construct and fit statistical, machine learning, or optimization models
  </li>
  <li>
   Write production modeling code; collaborate with Software Engineers to implement algorithms in production
  </li>
  <li>
   Design and implement both simulated and live traffic experiments
  </li>
  <li>
   Analyze experimental and observational data; communicate findings; facilitate launch decisions
  </li>
  <li>
   Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
  </li>
  <li>
   Drive collaboration and coordination with cross-functional teams
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Experience:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields
  </li>
  <li>
   2+ years professional experience in a technology company setting
  </li>
  <li>
   Proven experience with building and evaluating machine learning models
  </li>
  <li>
   Proficiency with Python and working in a production coding environment
  </li>
  <li>
   Passion for solving unstructured and non-standard mathematical problems
  </li>
  <li>
   End-to-end experience with data, including querying, aggregation, analysis, and visualization
  </li>
  <li>
   Strong oral and written communication skills, and ability to collaborate and communicate with others to solve a problem
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Great medical, dental, and vision insurance options with additional programs available when enrolled
  </li>
  <li>
   Mental health benefits
  </li>
  <li>
   Family building benefits
  </li>
  <li>
   Child care and pet benefits
  </li>
  <li>
   401(k) plan to help save for your future
  </li>
  <li>
   In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
  </li>
  <li>
   18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
  </li>
  <li>
   Subsidized commuter benefits
  </li>
  <li>
   Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
  <br/>
  <br/>
 </em>
 <em>
  Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule &mdash; Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
  <br/>
  <br/>
 </em>
 <em>
  The expected base pay range for this position in the New York City area is $128,000 -$160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
 </em>
</div>


Data Scientist, Algorithms, Optimization - Fulfillment

Roku

<div>
 <p>
  Teamwork makes the stream work.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Roku is changing how the world watches TV
  </strong>
 </p>
 <p>
  Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.
 </p>
 <p>
  From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the team
  </strong>
 </p>
 <p>
  The Core Analytics Team is a centralized function dedicated to providing data-driven insights to drive business and product success. We work closely with our Product, Engineering, and Marketing teams to deliver exceptional experiences to our customers while maximizing the value proposition for the business.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the role
  </strong>
 </p>
 <p>
  Roku is looking for a Data Scientist to join the Core Analytics team and provide support for our Customer Intelligence function, part of the broader Planning &amp; Optimization team. Together, we answer high-impact business questions from senior leaders with clear, decision-ready insights. You&rsquo;ll work on customer analytics that directly shape how Roku grows engagement, retention and monetization across the streaming ecosystem, with visibility to cross-functional leaders and meaningful ownership over high-impact questions.
 </p>
 <p>
  <br/>
 </p>
 <p>
  This role is more than analytics and is intentionally &ldquo;business-forward&rdquo;. We're looking for someone who can translate customer behavior into metrics and narratives which can help define our customer strategy, and/or measure the impact of initiatives on customer behavior. You&rsquo;ll be expected to translate ambiguous stakeholder needs into strong analytical narratives and executive-ready deliverables. Familiarity with causal inference/experimentation is important; deep specialization is a plus but not required. This is a hybrid role with four days per week in the office, Monday through Thursday. The selected candidate will be based out of NYC.
 </p>
 <p>
  For New York Only - The estimated annual salary for this position is between $135,000-$153,000 annually.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What you'll be doing
  </strong>
 </p>
 <ul>
  <li>
   Own end-to-end analyses: scope the question, define success metrics, pull data, analyze, synthesize, and deliver data-driven narratives.
  </li>
  <li>
   Drive stakeholder alignment: clarify objectives, assumptions, tradeoffs, and decision points; ensure outputs are usable.
  </li>
  <li>
   Build crisp storytelling &amp; presentations: create executive-ready readouts (slides, memos) with clear &ldquo;so what / now what.&rdquo;
  </li>
  <li>
   Develop SQL and Python-based workflows: write and review SQL/Python code to create datasets, compute KPIs, and validate results; use Airflow to maintain and build new pipelines when needed.
  </li>
  <li>
   Create reporting in Tableau/Looker: develop dashboards or recurring scorecards that make performance tracking easier and reduce ad-hoc churn.
  </li>
  <li>
   Measurement &amp; causal thinking: apply or partner on quasi-experimental approaches (e.g., diff-in-diff, propensity matching, synthetic controls) with appropriate caveats to address incrementality questions.
  </li>
  <li>
   Raise analytical quality: ensure statistical rigor, bias awareness, and clear limitations.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   We're excited if you have
  </strong>
 </p>
 <ul>
  <li>
   3+ years (or equivalent) in analytics/data science roles driving business decisions (tech, media, marketplaces, consumer products, etc.).
  </li>
  <li>
   Strong SQL (joins, window functions, building analysis-ready tables, QA/validation).
  </li>
  <li>
   Proficiency in Excel to work with data, tables and visualization.
  </li>
  <li>
   Strong ability to communicate insights: structured thinking, clear writing, confident presenting to non-technical and executive audiences.
  </li>
  <li>
   Solid foundation in statistics (hypothesis testing, confidence intervals, regression basics).
  </li>
  <li>
   Experienced with Python for analysis and data pipeline production (via Airflow).
  </li>
  <li>
   Hands-on experience with visualization tools like Tableau or Looker
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Our Hybrid Work Approach
  </strong>
 </p>
 <p>
  Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Benefits
  </strong>
 </p>
 <p>
  Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Our employees can take time off work for vacation and other personal reasons to balance their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Accommodations
  </strong>
 </p>
 <p>
  Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   The Roku Culture
  </strong>
 </p>
 <p>
  Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.
 </p>
 <p>
  We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
 </p>
 <p>
  To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.
 </p>
 <p>
  <br/>
 </p>
 <p>
  By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com.
 </p>
</div>


Explore 1076+ Senior data scientist in New York this March. Find roles across top companies and apply now to boost your career.

1076 senior data scientist jobs In New York

Senior Data Scientist Medical Analytics, Care Gaps & Customer Segmentation Team

Data Scientist

Data Scientist

Product Data Scientist - Crypto

Data Scientist, Product Analytics

Data Scientist, Algorithms, Optimization - Fulfillment

Data Scientist