Top Senior Data Science Jobs

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

The role involves analyzing fraud and risk data, defining KPIs, collaborating on anti-fraud strategies, and creating tools and dashboards for data accessibility at Whatnot.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead end-to-end direct mail marketing campaigns: define targeting and suppression logic, execute and validate data pipelines, manage offshore execution, measure ROI and experiment results, partner with marketing and third parties to optimize audiences and campaign performance, and present insights to senior leadership.

As a Staff Data Scientist at Gusto, you will drive data-informed decision-making, lead projects, collaborate with teams, and mentor others in statistical analysis and experimentation.

Apply statistical analysis, predictive modeling, experimentation, and AI-assisted methods to support product analytics for small business P&C insurance. Partner cross-functionally to build lead/trigger capabilities, measurement frameworks, and AI-enabled use cases to improve client outcomes and product performance.

Perform advanced analytics and AI/ML to generate actionable insights for auto finance products. Build predictive models, measurement frameworks, and conversational AI solutions; partner with Product, Technology, and business leaders to drive growth, present findings, and refine KPIs and A/B experiment designs.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, design A/B and bandit experiments, develop pricing automation (DealBot) and monitoring for AI-driven rate recommendations, own ETL/analysis/visualization, and partner with Finance, Risk, Product, and GTM teams to operationalize pricing intelligence.

The role involves managing data science projects focused on travel intelligence, leveraging machine learning and data analytics to improve customer experiences.

Lead analytics and measurement strategy for SPP, manage a team of ~3 data scientists, prioritize roadmap, develop cross-channel measurement and causal methods, drive automation and scalable dashboards, enforce reproducible code/data practices, and influence senior stakeholders to translate analytics into business impact.

Lead fraud risk strategy using advanced analytics: develop and implement models and metrics, analyze account lifecycle profitability, drive cross-functional initiatives, execute complex projects end-to-end, and present actionable insights to executive leadership to mitigate fraud.

Lead a team to design and execute analytics and test-and-learn programs for credit card products. Develop segmentation, campaign design, business case analytics, and MIS; present insights to senior stakeholders and evolve analytics tooling (Snowflake, AI-enabled apps).

Lead data science strategy for a commercial lending portfolio: build credit-risk and monitoring models, integrate GenAI, produce executive reporting, shape analytics and risk strategy, manage end-to-end projects, ensure quality/control, and mentor a team of data scientists and analysts.

Perform fraud analytics across the account lifecycle to identify risks and profitability drivers, develop monitoring and reporting, lead complex projects end-to-end, provide actionable recommendations, and communicate findings to stakeholders to guide fraud strategy and controls.

Lead credit-risk analytics for consumers and small businesses using large payment/customer data sets. Build attributes and models, deliver executive-ready insights, monitor emerging risks, prioritize high-impact projects, and identify GenAI opportunities to modernize analytics.

Lead people-analytics projects: analyze large HR datasets using statistical methods and ML (SAS/Python/R), build models and visualizations, deliver insights to stakeholders, and partner with data engineers and architects to operationalize solutions.

As a Data Scientist at Opendoor, you'll enhance pricing strategies through statistical models, machine learning, experiments, and interdisciplinary collaboration to drive business outcomes.

Lead end-to-end data science for lending products: define metrics, run experiments, build measurement systems, evaluate model and policy performance, use AI tools to accelerate analysis, and mentor the team while partnering with product, engineering, and risk stakeholders to drive credit product decisions.

Lead analytics and measurement for a Sales subdomain: monitor KPIs, investigate performance issues, design experiments, build data foundations and self-serve dashboards, use agentic AI to automate workflows, and communicate results to senior sales, finance, and operations stakeholders.

Lead analytics for a Sales subdomain: measure performance, investigate drivers, design experiments, and deliver end-to-end data science solutions. Build and maintain data foundations, self-serve dashboards, and communicate results to senior sales, finance, and operations stakeholders. Use agentic AI and modern GTM tooling to scale impact and improve decision-making.

The Senior/Staff Data Scientist will build and deploy predictive models for consumer decisioning and business optimization, focusing on machine learning and statistical modeling. Responsibilities include model development lifecycle, data exploration, collaboration with teams, and improving product outcomes.

Lead the Business Cards & Payments data science team to build and deploy ML solutions across the customer lifecycle. Partner with engineers and product managers, use Python, Spark, H2O, AWS and relational data to design, train, validate, and implement models that drive business outcomes and improve customer experience.

Partner with Digital Assets, Finance, Treasury, and Risk to design measurement frameworks, perform strategic analysis and modeling, build scalable SQL-driven automation and dashboards, analyze on-chain and finance data, create visualizations, and drive data-informed product decisions for USDC and related digital asset offerings.

As a Senior Associate Data Scientist, you'll partner with teams to analyze model risks, develop machine learning models, and enhance loss forecasting processes at Capital One.

Lead GTM data science initiatives to build revenue forecasting, causal inference analyses, and AI-enabled solutions that improve sales, retention, and expansion. Partner with Product, Growth, and Commercial teams to operationalize insights, communicate findings to stakeholders, and mentor junior data scientists.