Top Data Science Jobs in Boston, MA

The Data Scientist will analyze user behavior, create segmentation strategies, design experiments, and track business metrics to drive growth in a SaaS company.

As a Data Scientist, you will design and operationalize advanced analytics, develop scalable models, and collaborate with teams to enhance product capabilities in healthcare.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

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.

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

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.

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.

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.

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

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

Embed with a core business area to define right problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end to improve product, growth, AI, or partnerships.

Embedded within a business unit, the Data Scientist defines the right problems, builds metrics, analyses, reports, and experiments, and delivers data-driven recommendations and end-to-end execution to improve product, growth, AI/automation, or partnerships.

Work embedded in a business unit to define problems, run analyses, build reports and experiments, surface insights, and drive data-informed decisions end-to-end with product, growth, AI, or partnerships teams.

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

Embed within a core business area to define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed recommendations end-to-end with product, growth, and operations.

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

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.

Partner with clients to ingest, clean, transform, and validate data for aiCast. Build ETL/ELT pipelines, dashboards, and forecasting workflows. Deliver end-to-end implementations, troubleshoot data quality, and collaborate with engineering and success teams to enable production analytics and insights.

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.

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.

Develop and productionize advanced statistical and machine learning models (Bayesian, hierarchical, latent-variable) to analyze and predict consumer sensory preferences, harmonize multi-study sensory data, validate models, automate pipelines, and translate insights for R&D and product innovation across FMCG markets.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

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.

As a Staff Data Scientist, you'll develop and deploy machine learning models to enhance renter experiences and optimize property partnerships, collaborating across teams to translate data insights into actionable strategies.