Top Senior Data Science Jobs in Boston, MA

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

Embed within a core business area to define problems, build metrics and analyses, run experiments, generate insights from data, and drive decisions end-to-end to improve product, growth, AI/automation, or partnerships.

The Senior Data Scientist will develop machine learning systems for fraud prevention using behavioral data, collaborate across teams, and mentor junior scientists.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

Design, develop, and deploy causal inference and predictive models (uplift, synthetic control, DML) for customer loyalty, churn, and LTV. Build foundational data models and scalable features, perform large-scale SQL ETL, operationalize models in cloud, partner with stakeholders, and present insights to drive revenue and loyalty program optimization.

The role involves building and validating Marketing Mix Models and geo-experiments, managing measurement infrastructure, and communicating insights to stakeholders.

Customer-facing data scientist advising customers on experiment design, statistical methodology, and experimentation architecture; running and analyzing A/B tests; building scalable experimentation programs; creating repeatable frameworks and technical enablement; partnering with Sales, Solutions Engineering, Product, and Engineering to drive customer success.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

Develop and maintain predictive models and data pipelines for player evaluation, acquisition, development, and performance optimization. Communicate findings via reports and visualizations, collaborate with Baseball Systems to integrate analytics, drive applied research, and introduce novel methodologies to improve Baseball Operations decision-making.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Design and build predictive models, AI tools, and data visualizations for CMS healthcare initiatives. Analyze quantitative and qualitative data (Medicare claims, public datasets, web analytics), perform feature engineering, anomaly detection, and provide insights to support product design and price-transparency tools. Collaborate with designers, product owners, and engineers in an agile environment.

Activate and operationalize clinical data for analytics by designing data models, taxonomies, and a clinical feature store; build reusable data assets, documentation, and dashboards; ensure data quality and compliance; partner with stakeholders and data engineering to enable downstream analysts, data scientists, and business users.

The Principal Data Product Scientist will oversee data needs management, product ownership, and collaboration with scientific and engineering teams to enhance analytics and data governance in Immunology R&D.

As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.

Senior individual contributor who builds statistical models and experiments to optimize acquisition, conversion, retention, and lifetime value. Partners with Product, Marketing, and Engineering to define data requirements, analyze A/B tests, perform cohort and funnel analyses, communicate findings to stakeholders, and mentor junior team members while contributing to analytics best practices.

Build and maintain large commercial datasets and predictive/forecasting models (BigQuery, dbt, SQL, Python). Design causal and experimental analyses to measure promotion impact and price elasticity. Partner with commercial, finance, and executive stakeholders to inform pricing, distribution, and investment. Deploy LLMs and AI agents to classify unstructured data and build tools that democratize data access.

As a Senior Data Scientist, you will design and deploy machine learning and graph algorithms to enhance identity trust solutions, own end-to-end projects, and collaborate with product and engineering teams to improve KYC and compliance products.

As a Lead Data Scientist, you will design and implement scalable data pipelines and analytics capabilities while leading technical decisions across data workflows, ETL processes, and statistical modeling in the GCP environment.

The Senior Data Scientist will develop machine learning models, conduct A/B tests, and work with behavioral data to enhance customer engagement and partner ROI.

Lead data science for Yahoo Mail subscriptions: analyze acquisition, conversion, pricing, retention, and churn; design and analyze A/B and multivariate experiments; build predictive and clustering models; partner with product, engineering, design, and business teams to deliver data-driven growth and monetization insights.

Perform data collection, integration, modeling, analysis, and explanation to support federal law enforcement investigations. Build ETL/data pipelines and entity resolution, interface with customers, handle sensitive data, and contribute to R&D and shared capabilities while working on-site at government customer locations.

The Principal Data Scientist - Oncology will lead efforts in standardizing and connecting biomedical and clinical data through the development of scalable knowledge graph infrastructure and AI-Ready datasets.

Design and deploy scalable statistical and machine learning models on large health datasets (claims, EHR, pharmacy). Prototype NLP search, resolve identity/merge anomalies, collaborate with product, engineering and analytics to productionalize models, monitor performance, and drive data-driven product improvements.

Proactively explore RevenueCat's data to identify product opportunities, translate ambiguous problems into analyses and production-grade predictive/descriptive models, partner with Product and Engineering to ship data-powered features (LTV prediction, experimentation, benchmarking), define statistical approaches, iterate on models in production, and communicate insights to technical and non-technical audiences.