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

Lead commercial analytics to diagnose sell-through, pricing, promotions, assortment, and retailer execution. Build causal and incrementality measurement, design test-and-learn, support elasticity and margin analyses, and deliver executive-ready insights and frameworks to optimize revenue, margin, and promotional efficiency across channels and retailers.

Design, build, and own the full data platform (ingestion, modeling, CI/CD, orchestration, observability, and BI). Implement streaming and batch pipelines for IoT data, enable governed self-service, enforce data governance/privacy/security, evolve AI access patterns, and provide technical leadership and mentorship to data engineers and data scientists to deliver production-ready analytics and ML capabilities.

Conduct quantitative research using surveys, experiments, and advanced statistical methods for healthcare and life sciences client engagements. Analyze data, develop insights and visualizations, support rigorous research design, and translate findings into actionable recommendations. Collaborate with consulting teams and global delivery groups while ensuring research quality and communicating complex concepts to technical and non-technical audiences.

Owns the architecture and implementation of Absentia Labs’ biomedical data platform. Designs schema-driven models, scalable batch and streaming pipelines, and cloud-native infrastructure supporting machine learning workflows. Establishes data quality, validation, provenance, lineage, and versioning practices while partnering with scientists, ML engineers, and product leads. Provides architectural leadership, mentorship, and guidance on performance, cost, scalability, and correctness.

Build and lead enterprise data capabilities for a global biotechnology company. Design data architecture, pipelines, APIs, integrations, governance, master data management, analytics, and AI foundations across commercial, R&D, technical operations, quality, and corporate functions. Lead a high-performing team, deliver self-service reporting, partner with technology and business stakeholders, manage vendors, and ensure data security, quality, privacy, and regulatory compliance.

Leads an analytics team that integrates partner and business data to identify growth, retention, profitability, and performance drivers. Develops forecasts, business cases, measurement frameworks, visualizations, and executive recommendations. Partners with senior stakeholders across insurance, finance, pricing, product, digital, operations, and technology. Drives AI and automation adoption while mentoring analysts and leading complex cross-functional initiatives.

Analyze financial services and consumer datasets using statistical methods, quantitative models, and SQL to generate investment insights. Serve as a client-facing subject matter expert, support data trials, explain data methodologies, develop research materials, and collaborate with Product, Data Science, Technology, Commercial, and Client Success teams to improve data products and client adoption.

Lead the architecture and development of UKG’s Unified FinOps Data Platform. Build scalable cloud-native data products and pipelines for cloud billing, usage, cost allocation, forecasting, optimization, reporting, and unit economics across AWS and GCP. Establish governance, data quality, lineage, observability, CI/CD, and infrastructure-as-code standards. Support AI-enabled forecasting and optimization, collaborate with Finance and Engineering stakeholders, mentor engineers, and drive adoption of self-service reporting.

Build and maintain large-scale data pipelines and analytics platforms for EDA datacenter observability, telemetry, reliability analysis, and capacity forecasting. Develop batch and streaming workflows, data models, quality frameworks, monitoring, and retention strategies using metrics, logs, traces, and hardware health data. Partner with observability engineers, data scientists, analysts, and infrastructure teams to deliver scalable, reliable, discoverable datasets for analytical and predictive use cases.

Analyze deposit portfolio, customer, and market data to identify growth opportunities and optimize banking products. Build performance dashboards, develop statistical models and business cases, support pricing and product initiatives, and enhance data structures with Data Management. Partner cross-functionally with Finance, Marketing, Technology, Treasury, and Retail Administration while providing strategic insights to senior management.