Top Senior Data & Analytics Jobs in Boston, MA

The Analytics & Insights Consultant provides advanced analytical insights to operational leaders, translating data into actionable insights that guide decision-making. Responsibilities include delivering analytical outcomes, supporting complex initiatives, mentoring peers, and communicating implications clearly to stakeholders.

Lead Data Scientist responsible for guiding projects, mentoring a team, developing data-driven solutions, and collaborating across departments to drive insights.

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.

Manage the data architecture and strategic planning for the Sales team, optimizing processes through data and AI for targeting accounts and pricing strategies.

The Principal Data Analyst will manage pricing and profitability strategy for Workhuman's E-commerce store, leveraging data analysis and cross-functional collaboration to drive decision-making and implement improvements in pricing strategies.

This role focuses on post-sale technical execution, ensuring customer onboarding and deployment, driving customer consumption of products, writing production code, diagnosing issues, and expanding adoption across teams.

The Staff Analytics Engineer leads business intelligence initiatives, develops a governed semantic layer, and advocates for a data-driven culture while leveraging AI tools for analytics.

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

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

Design, build, and maintain scalable Spark-based ETL pipelines and computed tables in a central data lake. Integrate structured and unstructured IoT, sensor, and external data for analytics, model training, and dashboards. Collaborate with Data Science, Analytics, and ML teams to ensure reliable, high-quality customer-facing datasets.