Top Hybrid Data & Analytics Jobs in Boston, MA

Lead commercial analytics to diagnose sell-through, pricing, promotions, assortment, and retailer execution. Build causal measurement, test-and-learn designs, elasticity and incrementality analyses, and deliver executive-ready recommendations to optimize revenue, margin, and share.

The Senior Data Engineer will design and optimize large-scale batch and streaming data pipelines using Scala and Spark, oversee the data engineering lifecycle, and engage in technical discussions to improve system efficiency.

Oversee client proposals and projects, leveraging coding skills for data processes, mentoring teams, and identifying growth opportunities in life sciences.

The Director, Forecast & Research will lead forecasting, market research, and insights generation for Xenon's epilepsy portfolio, collaborating with cross-functional leaders to deliver actionable analytics.

Lead development of large-scale data analysis and validation workflows for autonomous driving ML. Design metrics, build datasets, run statistical error and regression analyses, collaborate with ML and software teams, and maintain AWS/Kubernetes orchestration for large-scale evaluation.

The role involves leading the IT compliance and CSV/CSA framework, ensuring regulatory compliance, managing audits and inspections, overseeing validation activities, and partnering with various stakeholders.

Turn complex data into actionable insights for National Accounts by performing statistical analysis, forecasting, modeling, and automated reporting. Build dashboards and executive presentations, diagnose data quality, partner with account teams, data engineers, and finance to influence decisions and track performance metrics.

Owner of the semantic layer: build and maintain core data models and metrics, run dbt orchestration with CI/CD and testing, implement reverse ETL pipelines, and enforce PHI access controls to keep data HIPAA-compliant.

Support and lead Pre-Award initiatives including process mapping, operational analysis, data modeling, KPI assessment, change management, and project management. Develop policies, training and communications, present findings to leadership, and coordinate cross-functional stakeholders to improve sponsored research administration.

Lead the design and evolution of the enterprise data platform, establish standards, mentor teams, and collaborate across departments to deliver high-quality data products.