Top Hybrid Data & Analytics Jobs in Boston, MA

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.

Develops data and investment applications for a cloud-based analytics platform. Translates business requirements into technical solutions, prototypes, integrations, tests, reports, and system designs. Onboards and validates structured and unstructured datasets, investigates data exceptions, and collaborates with investment teams, engineers, vendors, QA, and IT. Creates project documentation and supports automated testing using SQL and Python, with a focus on private-market investment decision-making.

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.

Supports client implementations by designing and troubleshooting data integrations across clients, vendors, banks, and health plans. Uses SQL, APIs, ETL frameworks, relational models, and data validation practices to maintain integrity and compliance. Leads automation, client conversion, integration, and process-improvement projects; coordinates agile delivery phases, requirements, documentation, and deployment. Provides technical consulting, mentors analysts and associates, and partners with architects, product owners, engineers, and client operations teams.

Analyze POS, loyalty, panel, and syndicated data to identify consumer and category insights. Develop assortment, item performance, and store-clustering recommendations that support sales, market share, and category growth. Partner with clients and business leaders on data-driven strategies, translate findings into business opportunities, and present performance reviews. Collaborate with sales, category management, and analytics teams on strategic planning.

Analyze POS, loyalty, panel, and syndicated data to uncover consumer and category insights. Develop assortment, item performance, store clustering, and growth strategies; translate findings into recommendations that improve sales, market share, and category growth. Present business performance reviews and collaborate with sales, category management, analytics teams, clients, and business leaders to support strategic planning.

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.

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.

Analyze catastrophic insurance claims data and validate financial and uncertainty models using statistical methods, simulations, and code in R or C++. Document methodologies, assess model accuracy, create visualizations and presentations, and communicate technical findings to internal and client-facing teams. The role focuses on catastrophe risk, probability, insurance concepts, and quantitative modeling.