Top Remote Senior Level Data Science Jobs in Boston, MA

The Senior Data Scientist will design and implement AI-enabled products using clinical trial data, mentor team members, and collaborate with stakeholders.

The Director of Data Science leads data science and machine learning initiatives for Commerce Media, translating complex problems into scalable solutions, mentoring teams, and communicating insights effectively across functions.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.

The Engineering Manager, Data Science will lead a team to drive machine learning initiatives in AdTech, focusing on optimization and modeling strategies to enhance client success and operational efficiency.

As a Senior Data Scientist, you will collaborate with cross-functional teams to drive AI/ML product development, analyze user data, and influence product strategies.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead design and deployment of graph ML and network-biology analyses to generate drug target hypotheses from RWD and multi-omic data. Prototype methods, integrate solutions with engineers, prioritize tasks, and communicate results to cross-functional stakeholders while championing data science best practices.