Top Senior Data Science Jobs

Lead GTM-focused data science initiatives: build revenue forecasts, apply causal inference, develop AI-enabled sales and retention solutions, partner with Product/Growth/Commercial teams, and translate analyses into scalable, automated workflows and executive-ready recommendations.

Partner with Growth, Marketing, Sales, and Product to measure and optimize marketing and growth initiatives. Build dashboards and scalable measurement frameworks, design experiments, analyze ROI and trends, provide actionable recommendations, and communicate results to technical and non-technical stakeholders.

Lead CRM marketing analytics for Seller and Owner verticals: build segmentation and personalization models, map customer journeys, design targeted campaigns, define KPIs, analyze consumer data, integrate CRM with other systems, collaborate with engineering and marketing to optimize engagement and drive revenue.

As a Staff Data Scientist, you'll drive data-driven insights, mentor junior staff, and integrate data science tools with engineering teams. You'll lead critical projects and represent data science in various settings.

Build models to predict infrastructure resource needs, analyze telemetry and usage to inform capacity planning, optimize compute provisioning and costs, collaborate with engineers and finance, and provide data-driven recommendations to improve infrastructure reliability and efficiency.

Design and deploy predictive forecasting and analytics to support Revenue operations. Build models for forecasting, churn, expansion, and pipeline analytics; create scalable dashboards; partner with Revenue Operations, Finance, and Data Engineering to improve data quality, KPI governance, and executive reporting to drive data-driven decisions and AI readiness.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Join a talent network connecting senior/staff data scientists with VC-backed startups. Work with product and engineering to design experiments, build predictive and causal models, productionize analytics, create dashboards, mentor teammates, and shape data strategy to drive product and business outcomes.

Join a SignalFire talent network to be matched with VC-backed startups seeking Senior/Staff Data Scientists. Responsibilities include experimental design and analysis, predictive and causal modeling, productionizing models, building metrics and dashboards, advising product and business teams, mentoring other data scientists, and shaping data strategy and tooling at fast-moving startups.

Lead analytics for Medicaid quality programs: build analytical frameworks, perform data analyses and causal inference to evaluate program impact, translate requirements into scalable data models, collaborate with cross-functional teams, and communicate findings and risks to stakeholders to drive quality improvements.

Lead marketing measurement strategy with MMM and MTA; design incrementality and experiment frameworks (geo experiments, lift studies); interpret modeling results for stakeholders; provide technical leadership in marketing data science and ensure privacy/HIPAA-compliant solutions for healthcare marketing.

The Data Scientist III will enhance cybersecurity operations using data science and machine learning techniques, developing analytical models, and integrating data from various sources to improve threat detection and monitoring.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Lead cross-functional data science initiatives for marketing, growth, and product. Design causal measurement and experimentation frameworks, build ML and uplift models for personalization and allocation, improve data quality and instrumentation, use AI-assisted tools to accelerate analysis, and mentor other data scientists while delivering clear, executive-level recommendations.

Collect, integrate, and prepare data from multiple sources; design data models, predictive algorithms, and ML solutions; build dashboards and visualizations; ensure data quality and support analytics for FBI financial management, client delivery, and business development.

Apply statistical and machine learning methods to workforce data to generate insights for talent, retention, and workforce planning. Build predictive models, dashboards, automated reporting, and support HCM implementations while ensuring data governance, privacy, and ethical use of employee data. Partner with HR, Finance, IT, and business leaders to translate analyses into actionable recommendations.

Support NGA analysts by designing scalable Python-driven data processes, performing exploratory and operational analyses, producing actionable insights and geospatial visualizations, and managing multiple projects to integrate findings into mission workflows.

As a Data Scientist in Marketing, you will enhance AI-driven marketing strategies, collaborate with teams to develop metrics, analyze marketing data, and recommend improvements for user engagement.

Lead advanced analytics and modeling efforts: develop queries, prepare data, design and validate predictive and prescriptive models, mentor junior staff, engage stakeholders, deliver insights and recommendations, and apply modern data science and big-data techniques across business functions.

Design and run exploratory analyses, build Python-based data pipelines, apply statistical modeling, graph algorithms and ML to multi-INT datasets, and develop interactive dashboards (Power BI/Tableau/Grafana). Mentor junior staff, brief senior leadership, and produce technical reports and documentation in a DoD/IC environment.

Owner of analytics for EHR, revenue cycle, and operations: design and run experiments, analyze financial and operational metrics, investigate billing and account issues, and deliver actionable insights to Product, Operations, Finance, and Customer Experience to improve accuracy, reduce friction, and support growth.

Develop and execute analyses, predictive models, and reporting to improve Medicare Star Ratings. Analyze large healthcare datasets, extract actionable insights, partner with clinical/operations/product/IT teams, and present recommendations to stakeholders.

Work cross-functionally in 6–8 week analytics sprints to build models and deliver actionable recommendations for profit optimization, demand estimation, price-sensitivity and counterfactual analyses. Communicate insights to leadership, prepare presentations, and integrate advanced Yield Management analytics into business decisions.

Lead client-facing data science efforts to develop AI/ML solutions (including LLMs/agentic AI), guide teammates, clean and model complex data, evaluate model accuracy, visualize results for leadership, and work on classified networks requiring TS/SCI clearance.

Design, refine, and operationalize geospatial analytic models to bring consistency and transparency to GEOINT analysis. Extract, transform, and structure complex datasets, automate workflows, build dashboards, integrate models with analytic platforms, and ensure tradecraft integrity and defensible scoring frameworks that withstand scrutiny.