Top Remote Senior Level Data & Analytics Jobs in Boston, MA

The Sr. Analytics Engineer at Philo is responsible for designing data models, governing business metrics, collaborating with stakeholders, and ensuring data quality and documentation for analytics purposes.

The Senior Data Scientist will lead care gap analyses and HCP segmentation strategies using real-world data, mentor team members, and communicate insights to support medical affairs.

As a Senior Data Scientist, you will analyze product usage, develop frameworks for user behavior, build statistical models, and collaborate with cross-functional teams to derive actionable insights and influence decision-making.

As a Data Solutions Architect, you will collaborate with clients to define business requirements, showcase AcuityMD's data solutions, and drive commercial effectiveness in MedTech sales through data expertise and presentations.

The Associate Principal will translate client needs into analytical specifications, ensure quality control of analytical outputs, and deliver clear insights while overseeing methodologies and clinical context research.

The Senior Data Engineer develops and maintains data pipelines, evaluates business requirements, integrates data, ensures quality, and collaborates with teams to fulfill data infrastructure needs.

The Senior BI Engineer will develop and maintain business intelligence solutions for CRM insights, leading dashboard automation and integrating complex data systems.

The Senior Data Analyst will provide high-quality analytics and insights for business strategies, automate reporting, and collaborate across teams to transform data into actionable insights.

Lead analytics strategy for a financial institution, ensuring compliance and driving marketing analytics through predictive modeling and team management.

Lead Toast's credit risk strategy, overseeing portfolio management, product growth, and analytics while ensuring compliance with regulations and mentoring analysts.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.