Top Hybrid Data & Analytics Jobs in Boston, MA

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 Director of Biostatistics leads a team in clinical research, developing statistical plans, collaborating across departments, and ensuring regulatory compliance.

The Data & Reporting Co-Op will assist in managing data for partners, improve data processes, analyze opportunities for growth, and communicate insights to stakeholders.

As a Senior Data Engineer, you'll design scalable data models, build automated ETL pipelines, and mentor junior engineers while collaborating across teams.

The role involves operating and improving AI-driven data quality pipelines, managing offshore teams, and ensuring data accuracy and reliability. Responsibilities include monitoring pipeline performance, refining rules, and collaborating across teams to enhance data operations.

Lead the development of scalable data platforms and analytics systems, overseeing teams in building data pipelines, advanced algorithms, and dashboards for data-driven decision making.

Lead analytical method validation and drive process excellence initiatives. Collaborate with CDMOs, support quality systems, and manage documentation for regulatory compliance.

Partner with Product and Customer Success to build and maintain Snowflake-backed dbt models, dashboards, and KPIs. Ensure data quality and governed semantic layers, enable self-service analytics, support recurring reporting and executive reviews, and align analytics with Applied AI and automation workflows.

The Manager of MDM leads projects for Master Data Management systems, working with teams to ensure successful client engagements in the pharmaceutical and life sciences sector.

As the Distinguished Architect, you will lead the design and implementation of CloudZero's next-generation data platform, focusing on streaming architecture, data modeling, and optimizing query engines to enhance cost attribution and performance at scale.