Top Analytics Jobs in Boston, MA

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 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.

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.

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.

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.

Leads advanced analytics across the organization, owning MAU forecasting and growth models, experimentation standards, and causal inference methods. Establishes analytical best practices, reviews high-stakes analyses, partners with data and product teams, and scales recurring work through AI tooling. Mentors data professionals and translates complex statistical findings into actionable leadership recommendations.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Performs audit-focused data extraction, analysis, and reporting using SQL, R, Python, SAS, Posit, and Snowflake. Supports internal and external audits, legal, compliance, and investigations by transforming complex datasets, identifying risks and trends, reviewing data models and process flows, and providing code feedback. Requires 5+ years of data analysis experience, a relevant bachelor’s degree, and strong querying and project management skills.

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.

Generate actionable customer and product insights by synthesizing large, complex datasets, developing hypotheses, conducting experimentation and analysis, and translating findings into strategic business decisions. Collaborate cross-functionally with analytics, engineering, data science, marketing, and product teams. Build dashboards and reports, identify trends and growth opportunities, communicate customer experience insights, and strengthen analytics capabilities across the organization.