Top Hybrid Data Science Jobs in Boston, MA

Leads the Small Commercial Product Design and Modeling data science function, managing data scientists and overseeing predictive analytics, statistical modeling, dashboards, and decision tools. Provides strategic direction, develops talent, partners with senior business stakeholders, and drives complex cross-functional initiatives across insurance business units. Owns delivery of technically advanced insights and tools supporting strategic decision-making, while shaping the broader data science community.

Uses advanced analytics, business intelligence, and data science to deliver strategic insights and solutions for AML and sanctions clients in banking and capital markets. Responsibilities include analyzing complex datasets, developing data pipelines and architecture, creating scalable visualization solutions, collaborating with teams, managing stakeholders, building client relationships, and solving complex problems. The role also involves mentoring and managing others while maintaining professional and technical standards.

Lead and grow a Data Science team for Provider Products, set analytical direction, own experimentation and measurement, review methods, partner with product and engineering, hire and develop data scientists, standardize analytics and integrate generative AI to improve workflows and outputs.

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.

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.

As a Data Science Manager, you will lead a team in developing personalized experiences through machine learning, aligning efforts with product and engineering to drive impact and innovation.

Lead Data Scientist will define goals and metrics for algorithm Test & Evaluation, research T&E methodology, lead vendor coordination, present analyses and results to stakeholders, and transition algorithms into software and real-time embedded systems.

Ten-week, full-time paid Data Science internship for current PhD students. Interns will build and evaluate modeling and analytics tools, integrate internal and external data sources, design data science models, and communicate results. Candidates must continue their PhD after the internship and may be evaluated for full-time roles upon graduation.

Develop and deploy production-grade AI, machine learning, and generative AI solutions for insurance business challenges. Responsibilities include building LLM applications, prompt engineering, RAG workflows, data pipelines, experiments, proof-of-concepts, and scalable AI systems. The role involves monitoring model performance, generating business insights, collaborating with stakeholders, and communicating technical findings to diverse audiences.