Top Hybrid Data Science Jobs

Leads client-facing data science and analytics initiatives, translating complex marketing and media data into actionable business narratives. Develops measurement strategies, including test/holdout incrementality, informs acquisition and retention decisions, scales analytics best practices, and manages analyst teams. Partners with Sales, Client Services, Operations, and other stakeholders while supporting predictive and adaptive AI/ML solutions. The role requires strong client communication, strategic leadership, analytics expertise, and proficiency with Python, SQL, Tableau, and related tools.

Lead Vercel’s consumption forecasting strategy and end-to-end machine learning systems across infrastructure products. Develop advanced time-series, probabilistic, hierarchical, causal, and predictive models for operational and financial planning. Build scalable tooling for backtesting, monitoring, drift detection, retraining, and explainability. Partner with Finance, Infrastructure, Product, and GTM leadership on revenue planning, capacity optimization, pricing, and adoption scenarios. Set technical standards, influence organizational ML practices, and mentor senior data scientists and ML engineers.

Lead and build a greenfield marketing measurement function across B2C and B2B. Own attribution, incrementality, MMM, MTA, LTV, and experimentation; hire and mentor data scientists; partner with marketing leadership to turn statistical results into investment decisions; integrate measurement with data platform and GenAI tools.

Lead Data Scientist partners with business leaders to identify opportunities, design, develop, and deploy advanced analytics and ML solutions. Responsibilities include data preparation, modeling, feature engineering, delivering insights and visualizations, establishing standards, and directing associate data scientists, contractors, and consultants to produce measurable business value.

Build predictive models for churn, expansion, and look-alikes; run marketing mix and incrementality analyses; create leading indicators and cohort reporting; partner with Sales, Marketing, and RevOps to translate analytics into actionable recommendations and inform data infrastructure needs.

Lead and grow a data science team focused on provider experience. Define strategy, build roadmaps, run analyses, experiments, and predictive models, surface insights, and partner cross-functionally to drive measurable improvements in provider engagement and product experience.

The Senior Data Scientist will implement and test ML models for international products, collaborating with cross-functional teams to drive insights and deploy solutions.

Leads the strategy for scaling data science analyses used in pharmaceutical asset acquisition and diligence. Directs cross-functional Data Science and Engineering teams, determines which one-off analyses should become landscape analyses or durable tools, sets roadmaps, evaluates statistical and technical validity, identifies AI opportunities, and connects scientific findings to business impact, asset valuation, and sourcing decisions.

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.

Leads enterprise data, AI readiness, analytics, and data science strategy. Builds and manages teams across data engineering, analytics, and machine learning; oversees data pipelines, warehouses, lakes, MLOps, feature stores, predictive models, governance, compliance, executive dashboards, and experimentation frameworks. Partners with business leaders to identify AI opportunities, improve data literacy, and establish a company-wide data-driven culture.