Top Senior Analytics Jobs in Boston, MA

Leads product analytics across core product, hardware, and algorithms while managing and developing analysts. Partners with cross-functional teams to define KPIs, evaluate experiments, analyze member behavior and product performance, build scalable analytics processes, and influence product strategy through actionable insights. The role requires hands-on analysis, advanced SQL, data warehousing expertise, strong storytelling, and the ability to guide senior stakeholders and technical teams.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

Leads predictive media measurement across digital and traditional channels, building marketing mix, attribution, incrementality, and forecasting models. Owns KPIs, dashboards, signal detection, audience and creative effectiveness, brand health, and ambassador evaluation. Translates complex analytics into recommendations that optimize media allocation and marketing performance. Partners with agencies, marketing, brand, data, and engineering teams; mentors junior analysts and drives data-informed decisions across global markets.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

Lead strategic revenue cycle analyses to diagnose patient billing and collections performance, quantify ROI and value, build executive-ready recommendations and playbooks, partner cross-functionally, and mentor teammates to drive scalable, data-driven improvements.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Lead analytical support for performance marketing by evaluating CAC, ROAS, LTV, conversion, retention, and acquisition efficiency. Conduct deep-dive analyses, experimentation, incrementality studies, and marketing measurement using SQL, Python, and visualization tools. Build scalable reporting frameworks, improve data quality, communicate insights to senior stakeholders, influence channel and budget decisions, and mentor junior analysts.

Lead growth analytics for Zendesk’s product-led growth motion, guiding a team of analysts and partnering with Product, Engineering, Sales, Marketing, and Data teams. Define funnel metrics, measurement plans, experiments, and instrumentation across acquisition, activation, conversion, retention, and expansion. Analyze customer behavior using segmentation, cohorts, funnels, experimentation, and statistical methods. Improve self-service reporting, dashboards, metric definitions, reusable datasets, and analytics capabilities while coaching analysts and influencing senior stakeholders.

Lead advanced product analytics for a consumer product team by analyzing complex data, designing experiments, applying statistical and causal inference methods, developing metrics and reporting tools, and delivering actionable recommendations to cross-functional stakeholders and senior leadership. The role requires strong Python or R and SQL skills, product analytics experience, AI-assisted analytics proficiency, and the ability to influence product strategy.

Leads the design and delivery of scalable analytics solutions using Azure Databricks, Power BI, and related platforms. Transforms and validates structured and unstructured data, applies statistical techniques, develops dashboards and analytical models, and implements data governance and quality processes. Partners with business and technology stakeholders to translate requirements into technical solutions, provides peer guidance, monitors data trends, and communicates actionable insights to technical and non-technical audiences.

Lead the firm’s analytics strategy, roadmap, and growing analyst team. Partner with executives and law firm operations leaders to define KPIs, evaluate performance, identify bottlenecks, build forecasting and predictive capabilities, and translate data into business actions. Guide SQL, Python/R, statistical modeling, visualization, data quality, and analytics infrastructure standards while partnering with technology and data engineering teams to embed insights into operational workflows.

Own the analytical function for a core business area, defining business questions, metrics, reports, analyses, experiments, and recommendations. Partner with product, growth, finance, and operations leaders to drive decisions and measurable outcomes. The role requires solving ambiguous problems, independently structuring and interpreting data, communicating insights persuasively, and executing initiatives end to end.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, build reports, analyze data, design experiments, generate insights, influence leadership decisions, and drive initiatives through execution. The role requires strong first-principles thinking, independent data skills, persuasive communication, and ownership of ambiguous, high-impact problems.

Own the digital measurement ecosystem across websites, quote engines, customer portals, and account applications. Lead Google Tag Manager tracking frameworks, data-layer standards, Google Analytics 4 configuration, conversion events, attribution, funnel analysis, experimentation measurement, data-quality audits, and analytics governance. Partner with Marketing, Product, Engineering, and Data teams to translate customer behavior into actionable insights that improve growth, conversion, and customer experience.

Develop and maintain investment data solutions, quantitative models, performance attribution systems, dashboards, and reporting workflows. Partner with investment professionals to translate analytical needs into reliable data products supporting portfolio construction, manager selection, risk analysis, and research. Automate processes, improve data quality, apply model governance, and collaborate with technology and risk teams across global offices.

Leads College Board’s Operations analytics strategy and team, developing forecasting, predictive modeling, optimization, cost assessment, and decision-support capabilities. Partners with senior leaders across Operations, Product, Program, Technology, and Finance to improve execution, customer experience, efficiency, and cost savings. Responsibilities include setting technical direction, embedding analytics into operational decisions, presenting insights, hiring and coaching analytics staff, and building future AI and data-infrastructure capabilities.

Own supplier-side pricing, yield, monetization, retention, and churn analytics for a B2B marketplace. Build predictive models, data models, dashboards, cohort analyses, and A/B tests using SQL, Snowflake, dbt, and Looker. Partner with product, operations, engineering, sales, finance, and leadership to identify pricing and revenue opportunities, improve supplier retention, and translate marketplace insights into measurable business impact.

Lead and develop a team of partnership analysts; translate business questions into analytical frameworks, experiments, forecasts, and ROI models. Build dashboards and reporting infrastructure, analyze cohorts, funnels, retention, and partner performance, and own measurement frameworks for growth initiatives. Partner with Business Development, Engineering, Product, and Marketing to shape partnership strategy and communicate data-driven insights to technical and non-technical leaders.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

The Senior Data Scientist will analyze product data, design A/B tests, define KPIs, and collaborate with teams to improve product performance and user experience.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.