Top Data Science Jobs in Boston, MA

Lead analytics initiatives to deliver strategic insights for consumer markets. Develop advanced analytics and BI solutions, manage teams, engage stakeholders, implement cloud analytics, and coach diverse teams to improve performance and decision-making.

Analyze billing patterns, healthcare claims, and complex datasets to identify anomalies, audit data integrity, and support Trust and Safety initiatives. Build risk-monitoring pipelines and compliance dashboards using SQL, Python/R, and visualization tools. Translate technical findings into risk assessments for legal, compliance, and executive partners while developing safeguards to protect patients, regulatory standing, and platform operations.

Own analytics for Bevi digital experiences and websites, measure incremental impact of new flavors using experiments and quasi-experimental methods, build a flavor recommendation engine, create dashboards, and partner with Product, Design, Engineering, and Data Engineering to improve tracking, data quality, and product decisions.

Build and productionize end-to-end fraud and financial risk models: data acquisition, feature engineering, labeling, training, experimentation, deployment, and monitoring. Research new fraud types, drive product development, support data quality and access, and present analyses to inform product, operations, sales, and marketing.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

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 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.

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.

Researches, develops, evaluates, and integrates AI and machine learning models for national security applications. Analyzes multimodal datasets, including text, imagery, geospatial, time series, and social media data, to identify patterns and generate intelligence insights. Collaborates with researchers, engineers, domain experts, customers, and end users; communicates findings, defines requirements, responds to feedback, and mentors teammates. Work primarily occurs onsite in Woburn, Massachusetts, or Arlington, Virginia.

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

Collects, explores, and analyzes large datasets to identify business opportunities and improve outcomes. Develops predictive models, machine-learning algorithms, testing frameworks, and data pipelines; evaluates data quality and model performance; and communicates actionable insights to stakeholders and clients. The role also manages data science projects, establishes reporting best practices, and collaborates with cross-functional teams to implement and monitor solutions.

Develops and enhances financial crime risk models and AI solutions supporting AML/CTF compliance. Collects, prepares, analyzes, and visualizes data; applies statistical modeling and machine learning to uncover insights and solve business problems. Collaborates with analysts, engineers, and developers to build scalable data science solutions, communicates findings to technical and non-technical stakeholders, supports model governance and risk management, and contributes to regulatory and cross-functional initiatives.

Embed with a business unit to define analytic problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end using SQL/Python.

Embedded in a core business area, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions to improve product, growth, AI/automation, or partnerships.

Embedded data scientist owning analytics end-to-end for a business unit: define problems and metrics, pull and analyze data, design experiments, build reports, surface insights, and drive recommendations that influence product, growth, and strategic decisions.

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

Embedded within a core business area, define analytics problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end with stakeholders.

Embed on a core business team to define problems, build metrics/reports, run analyses and experiments, and drive data-informed recommendations end-to-end to improve growth, product, AI/automation, or partnerships.

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 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.

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

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.

Analyze, clean, and validate complex healthcare data; develop statistical, machine learning, and AI models; implement agentic workflows, RAG solutions, and model fine-tuning; deploy and monitor models in production; collaborate with technical and business teams; conduct research; and document and communicate findings.

Design and build thermal performance analytics, Python-based engineering models, scalable data flows, and Edge-native applications for power plant asset performance management. Integrate historian, cloud, Edge, and industrial systems; develop automation, diagnostics, KPI validation, and root-cause workflows; support customer deployments; and lead architecture discussions while mentoring engineering teams.