Top Remote Senior Level Data Science Jobs in Boston, MA

Lead the data science and data engineering team at Sword Predict, focusing on machine learning model design and team management while acting as a technical expert in client engagements.

Develop and scale AI-powered features for Vendelux's platform, focusing on data-driven solutions and enhancing user experience in event marketing.

Design, test, and deploy time‑series and econometric forecasting models; own end‑to‑end model lifecycle (feature engineering, deployment, monitoring); analyze large datasets to surface drivers; translate results into clear insights for leadership; partner cross‑functionally to scale forecasting capabilities and improve shared tools and pipelines.

The Lead Data Scientist will develop advanced analytical solutions for pricing and customer insights in pet insurance, mentor teams, and collaborate with stakeholders.

The Senior Data Scientist will analyze DeFi and stablecoin data to enhance understanding of liquidity and market behaviors, create dashboards, and develop measurement frameworks in collaboration with various teams.

The Senior Data Scientist will develop models and analyses for risk and revenue decisions, collaborating with various teams to optimize funding for eCommerce.

Seeking a Senior Data Scientist with experience in machine learning and generative AI to design, build, and deploy models to improve healthcare outcomes. Responsibilities include developing analytics solutions, working with diverse healthcare data, and mentoring clients.

As a Senior BI Analyst, you will execute data analytics projects, utilizing BI tools for data extraction, reporting, and visualization while collaborating with clients and internal teams.

Lead the Data Science team to execute complex technical initiatives, manage model development, and define strategic priorities for growth. Collaborate with cross-functional teams and maintain high standards in model validation and product delivery.

The role involves owning the complete data science lifecycle from analysis to model deployment, focusing on logistics-related predictive models and collaborating with an ML Engineer.