Top Analytics Jobs in Boston, MA

Own commercial analytics for direct-to-consumer and marketplace channels, analyzing pricing, promotions, conversion funnels, merchandising, product mix, customer behavior, and channel economics. Build scalable reporting tools, support forecasting and planning, and translate transactional and behavioral data into recommendations for digital commerce leadership. Partner with Marketing Analytics and Analytics Engineering to connect acquisition trends with commercial outcomes and ensure trusted data.

Leads and scales Hi Marley’s analytics function, managing analysts and hiring as the team grows. Establishes trusted company metrics, self-service analytics, standards, and an analytics roadmap. Partners with Product, Customer Success, Growth, Marketing, Finance, and Data Engineering on product, customer, revenue, financial, billing, marketing, experimentation, and utilization analysis. Develops people, communicates insights to executives, and drives data-informed decisions across the organization.

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.

This co-op develops analytical solutions for fulfillment performance reporting. Responsibilities include understanding fulfillment processes, consulting on data pipelines, developing data models and dashboards, analyzing trends, and providing insights and recommendations. The role collaborates with product managers, visualization analysts, data scientists, IT, technical teams, and fulfillment operations.

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.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Supports cross-channel marketing attribution and influence modeling by documenting data sources, defining business rules, mapping and normalizing interaction data, testing reporting prototypes, and recommending implementation steps. The intern also assists with AWS marketing data organization, segmentation research, data hygiene, process documentation, and stakeholder communications. The role requires analytical thinking, thorough documentation, clear communication, and collaboration across marketing and technical teams.

Leads Customer Success analytics strategy, executive business reviews, customer experience and voice-of-customer insights, enablement impact measurement, and data foundation development. Manages two analysts, partners with data engineering and data science, applies statistical and experimental methods, analyzes structured and unstructured customer data, and uses AI tooling to improve self-service and recurring analytics. Translates ambiguous business questions into actionable recommendations for senior leaders.

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 complex workforce data to produce executive-ready dashboards, visualizations, models, and actionable insights. Transform multi-source datasets, apply regression and machine learning techniques, and use Databricks, Tableau, Power BI, R, Python, and SQL. Own analytical deliverables from problem definition through executive communication, ensuring data quality and scalability while partnering with HR, business leaders, and senior stakeholders.

Acts as a data analytics domain expert delivering research, statistical analysis, and predictive insights for business decisions. Translates business problems into quantitative solutions, analyzes large datasets, develops scalable data workflows, and uses SQL, Python, Alteryx, Tableau, and Power BI. Collaborates with stakeholders and leadership to communicate findings and drive actionable outcomes across multiple projects. This is an individual contributor role without direct people management responsibilities.

Develop and lead data-driven analytics initiatives for Fidelity Digital Assets. Analyze structured and unstructured data, create dashboards and reporting capabilities, apply statistical methods, and communicate insights that guide business decisions. Partner with product, operations, and other teams to improve digital asset offerings and customer experiences. The role requires expertise with SQL, Python or R, visualization tools, big data technologies, and digital analytics platforms.

Own end-to-end analytics for a business area such as growth, product, AI, or partnerships. Define business questions and metrics, build reports, conduct analyses and experiments, generate actionable insights, and influence product, growth, finance, and operations decisions. The role requires independent data work, first-principles problem solving, clear communication, and ownership of ambiguous initiatives through execution.

Own end-to-end analytics for a business unit across growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; translate findings into recommendations; influence stakeholders; and drive execution toward measurable business outcomes. The role requires first-principles problem solving, strong communication, independent data work, and comfort with SQL or Python.

Conduct quantitative research across systematic investment strategies, analyzing large datasets, portfolio risks, signals, and fund outcomes. Develop analytics, KPIs, reporting mechanisms, and tools used by portfolio managers and researchers. Partner with quantitative researchers, traders, technologists, and portfolio managers to uncover insights and improve decision-making. Apply statistical techniques, programming, risk management, and modern AI tooling to solve complex problems.

Leads the Journey Intelligence Team’s analytical strategy, manages analysts, develops customer measurement frameworks and segmentation, conducts exploratory and experimental analysis, and translates customer behavior insights into strategic initiatives that improve engagement and the end-to-end customer experience.

Leads commercial analytics across digital commerce, apparel and accessories, and wholesale. Manages analysts, owns bookings forecasting, develops customer and channel economics frameworks, and builds scenario-planning and measurement models. Partners with Finance and senior stakeholders to evaluate growth opportunities, diagnose performance, quantify tradeoffs, and guide investment decisions. Requires strong SQL, analytical modeling, people leadership, and cross-functional business judgment.

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 healthcare implementation projects, business workflow documentation, process improvement, work plans, and deliverables. Reviews large datasets from multiple sources to identify outliers, monitor trends, and prepare state-mandated reports. The internship provides experiential learning for undergraduate students interested in healthcare or data analytics.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Analyze startup user and product data, identify trends and drivers, and turn findings into strategic recommendations. The role owns key metrics and dashboards, leads analytical deep dives, sizes opportunities, evaluates product tradeoffs, supports roadmap prioritization, and develops external-facing insights about startups in partnership with marketing and communications.

Develop and maintain Medicaid enrollment data and reporting solutions. Write advanced SQL queries, build databases, validate and transform high-volume data, troubleshoot data-quality issues, support audits and testing, and improve controls and processes. Translate Medicaid business requirements into scalable technical solutions and communicate actionable insights, risks, and recommendations to stakeholders.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.