Top Hybrid Data Analysis Jobs in Boston, MA

The Allocation Analyst supports the Wholesale Planning function by executing allocation strategies, analyzing inventory data, collaborating with cross-functional teams, and recommending adjustments to maximize sales and minimize excess inventory.

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.

Lead the integration of advanced imaging analytics and AI in drug development, focusing on medical image analysis and clinical trials.

The Senior Pricing and Packaging Analyst will analyze data to inform pricing strategies, develop recommendations, and work collaboratively across teams to implement these strategies.

As a Senior Analyst, you'll analyze customer behavior, evaluate promotional strategies, and provide data-driven insights to influence key business decisions at DraftKings.

Lead data-driven diligence and value-creation analytics for private equity and corporate clients. Manage complex analyses, build pipelines and warehouses, develop predictive models, improve data quality, create visualizations (Alteryx, Power BI, Tableau), and coach teams to deliver actionable insights throughout the deal lifecycle.

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

Lead prospect research, pipeline development, and due diligence to identify and prioritize major gift prospects. Conduct in-depth donor research, prepare concise briefing products, analyze wealth and philanthropic data, integrate AI tools responsibly, and collaborate with fundraisers to inform portfolio strategy and gift acceptance decisions.

The Biostatistics Director will oversee biostatistical functions, manage teams, and direct complex projects in drug development, contributing technical insights and leading collaborations.

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.