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

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.

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.

Analyzes business requirements and defines functional specifications for small to moderate projects. Translates requirements into functional designs, test plans, documentation, and user materials. Coordinates with IT to resolve issues and improve business processes. Supports application testing through traceability analysis, test preparation, script writing, and functional test execution. May guide less experienced colleagues.

Own executive reporting and data strategy for autonomous vehicle system performance. Lead the weekly Software Performance Review, develop board-level reporting, analyze robotics and autonomy metrics, translate technical findings into strategic recommendations, and establish data visualization standards. Partner cross-functionally across engineering and performance teams, create data-driven feedback loops, and mentor Business Analytics and Business Intelligence engineers.

Conduct media mix modeling, experimentation, incrementality analysis, forecasting, and marketing performance reporting. Build scalable analytical tools, automated workflows, Tableau dashboards, and statistical resources using SQL, Python, and BI platforms. Partner with Marketing, Data Science, Data Engineering, Finance, and Sales teams to improve measurement capabilities, operationalize data structures, and translate complex findings into actionable business recommendations. Maintain analytical standards, documentation, and quality controls.

Lead and mentor a product analytics team that diagnoses product performance, evaluates launches, defines trusted KPIs, and drives strategic decisions. Oversee rigorous experimentation, causal inference, cohort analysis, metric governance, and telemetry standards. Partner with Product, Engineering, Marketing, Growth, Design, and Finance leaders to translate analysis into recommendations. Promote AI-native workflows using tools such as Claude Code while ensuring analytical quality, code validation, and clear executive communication.

Supports client portal data, reporting, dashboards, and visualizations for investment data. Translates business needs into requirements, mappings, user stories, and acceptance criteria; validates Power BI and Snowflake data; performs reconciliation and root-cause analysis; supports production incidents, releases, and documentation; and coordinates an offshore support partner across priorities, testing, issue resolution, and operational readiness.

Leads commercial data governance strategy, operating models, policies, standards, ownership, stewardship, metadata, lineage, and data-quality programs. Partners with cross-functional stakeholders to improve data integrity, accessibility, privacy, compliance, and responsible use. Oversees governance councils, catalogs, glossaries, issue remediation, performance metrics, tool adoption, training, and change management across a regulated biotechnology commercial organization.

Manages research data acquisition, licensing, contracts, vendor relationships, governance, and compliance at Harvard Kennedy School. Leads data safety staff, evaluates contractual and privacy risks, develops data management plans and SOPs, oversees access and disposition workflows, and advises researchers and institutional stakeholders on data-use obligations, regulatory requirements, and risk mitigation.