Top Hybrid Data Analysis Jobs in Boston, MA

Leads complex workforce analytics and strategic workforce planning initiatives for a Technology organization. Analyzes workforce, business, financial, talent, skills, and labor-market data; develops models, scenarios, and executive insights; advises senior leaders; influences workforce decisions; and advances analytics methodologies, tools, and capabilities. The role also mentors peers and manages multiple cross-functional workstreams amid ambiguity.

Leads the Journey Intelligence Team’s analytics strategy, develops analysts, and builds measurement frameworks, segmentation strategies, and scalable data assets. Conducts exploratory analysis, experimentation, and customer lifecycle research to identify engagement opportunities. Partners with Product, Operations, and senior leadership to translate customer behavior insights into strategic initiatives and measurable improvements across the customer journey.

Performs data analysis, cleans and validates data, identifies trends and anomalies, builds dashboards and reports, and supports KPI development. Collaborates with engineers and business stakeholders to improve data quality, pipelines, reporting requirements, and analytical processes. Leads data-driven change management, communicates insights, shares best practices, and may support urgent IT incidents.

Develop market intelligence, forecasting, statistical models, scenario analyses, and automated reporting for supply chain decisions. Integrate internal and external datasets using Python, R, SQL, and other tools; build dashboards; support data governance; and translate analytical findings into recommendations for procurement, planning, and executive stakeholders.

The AI Analyst Co-op will use Python, HTML, SQL, APIs, and AI tools to generate scalable insights for go-to-market teams. Responsibilities include personalizing BDR outreach by buyer persona, distributing market insights across sales, marketing, and partner resources, and collaborating with Platform Advisory. The role requires strong analytical skills, attention to detail, problem-solving persistence, and an understanding of technology’s role in improving operational efficiency.

Conduct healthcare product analysis, build dashboards and recurring reports, monitor KPIs, support A/B testing, validate data, and identify trends affecting member engagement and health outcomes. Partner with product, engineering, design, data science, and marketing teams to deliver actionable insights, improve data quality, and support healthcare product strategy. The role also contributes to documentation, segmentation analysis, and repeatable analytics processes.

Own high-impact revenue strategy analyses from problem framing through recommendations and decision support. Analyze marketplace performance, lead economics, monetization, retention, product adoption, and operating models using SQL, Python, financial modeling, and cross-functional data. Advise senior leaders, create executive- and board-ready materials, improve metric reliability, build reusable analytical frameworks, and influence decisions across Revenue, Product, Finance, and Operations.

The Data Scientist II will lead and execute health economic outcomes research projects, collaborate with stakeholders, and build analytical infrastructure while adhering to regulations.

As a Decision Analytics Associate Consultant, you will develop statistical models, apply analytic techniques, and communicate results to clients. You will also design custom analyses and guide team projects while mentoring Associates and maintaining client relationships.

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics practices.