Top Data Science Jobs in Boston, MA

Lead and manage data science teams to build ML and deep learning models, maintain data pipelines and lakes, ensure data quality, deliver actionable insights, and manage project timelines and client expectations.

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.

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.

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

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

As a Senior Data Scientist, you will develop technologies for signals exploitation, perform data analysis, and implement algorithms while collaborating with project teams.

Embedded in a core business area, you'll define problems, build analyses, metrics, reports and experiments, surface insights, and drive data-informed product, growth, AI, or partnerships outcomes end-to-end.

Embedded on a core business team, the Associate Data Scientist defines questions, builds metrics/reports, runs analyses and experiments, surfaces insights, and drives data-informed recommendations end-to-end to impact product, growth, AI/automation, or partnerships.

Embedded data scientist owning analytics for a core business area: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end.

Embedded on a core business unit, you will define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embed with a business unit to define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed product, growth, AI, or partnership outcomes end-to-end.

Embedded within a core business area, you will define the right problems, design metrics and experiments, pull and analyze data, build reports, and surface insights. You will make recommendations, secure stakeholder buy-in, and drive execution to improve product, growth, automation, or partnership outcomes.

Seeking a Data Scientist to analyze healthcare data, design models, and communicate insights to improve financial outcomes and member care. Requires strong technical expertise and collaboration across functions.

Develop and maintain predictive models and data pipelines to support player evaluation, acquisition, development, and performance optimization. Produce clear reports and visualizations, communicate findings to technical and non-technical stakeholders, integrate analytics with team systems, monitor data quality, and evaluate cutting-edge research to recommend improvements that enhance on-field performance.

Lead data science projects to optimize drug development, develop AI models for clinical trials, and collaborate with teams on biomedical workflows.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

The Data Scientist II will lead RWE studies, derive insights from real-world clinical data, and contribute to methodologies using advanced statistical techniques and AI tools, collaborating closely with pharmaceutical partners.

Lead and scale enterprise data science capabilities for operations-focused use cases in pharma. Build and deploy production ML/AI and optimization solutions, design reusable ML platforms, engage stakeholders to translate problems into high-impact analytics, and mentor teams while driving adoption and lifecycle management of digital products.

Perform quantitative real estate and urban economic analysis, applying econometric and spatial methods to synthesize property, macroeconomic, and geospatial data. Build and maintain automated data pipelines, ensure data integrity, document dataflows, and prototype ML/AI methods. Collaborate with research, GIS, and engineering teams to produce reproducible insights and analytical products for stakeholders.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Embedded within a business unit, own end-to-end analytics: define problems, build metrics, run analyses and experiments, produce reports, and drive recommendations to product, growth, and partnerships using SQL/Python. Communicate findings to stakeholders and ensure data-driven decision-making and measurable outcomes.

Embedded Data Scientist responsible for defining problems, building metrics, analyses, experiments and reports, and driving data-informed recommendations and outcomes across growth, product, AI/automation, and partnerships. You'll execute end-to-end, influence stakeholders, and deliver measurable impact using SQL, Python, Metabase, and Jupyter Hub.

Design and implement quantitative behavior metrics for autonomous vehicles, build and maintain data pipelines and dashboards, analyze large-scale vehicle logs and simulation data to identify regressions, set metric thresholds to support geofence expansion, and communicate findings to technical and non-technical stakeholders.

The Sr. Football Data Scientist will build, deploy, and refine analytical models for football insights, managing large datasets and collaborating with teams for high-quality analytics solutions.

Develop and operationalize graph-based analytics for fraud detection and investigative analysis. Build graph models, apply graph algorithms and ML to detect anomalies, support entity resolution, create visualizations and dashboards, and collaborate with investigators and stakeholders to deploy and maintain production solutions.