Top Senior Analytics Jobs in Boston, MA

Conduct independent, high-complexity analytics for Liberty Mutual’s Embedded Channel. Apply advanced statistical techniques, predictive modeling, A/B testing, and complex data analysis to optimize funnels, questionnaire design, and underwriting defaults. Build analytic tools, manage research projects, synthesize diverse data sources, and deliver actionable recommendations. Present findings to senior leadership and influence decisions affecting profitability, growth, and customer satisfaction.

Conduct independent, high-complexity analytics for Liberty Mutual’s Embedded Channel, focusing on funnel optimization, A/B testing, questionnaire design, underwriting defaults, and predictive modeling. The role synthesizes complex data, develops analytical tools, manages research projects, and presents actionable recommendations to senior leadership that influence growth, profitability, and customer satisfaction.

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.

Perform financial due diligence data analytics for middle-market M&A: obtain, validate, normalize, analyze transaction data (revenue, costs, inventory), produce dashboards and visualizations, identify trends/outliers, and communicate insights to deal teams and clients.

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.

Own the end-to-end analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, build reports, analyze data, design experiments, surface insights, and drive recommendations through execution. Partner with product, growth, finance, and operations leaders to influence decisions and improve key business outcomes.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; surface actionable insights; influence leadership decisions; and drive initiatives through execution. The role requires first-principles problem solving, strong data skills, persuasive communication, and end-to-end ownership of ambiguous business problems.

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.

Own paid social measurement and analytics across brand, consideration, and performance campaigns. Execute Conversion Lift and Brand Lift Studies, design geo-randomized experiments with data science, build KPI dashboards, evaluate creative and audience performance, and recommend budget and strategy changes. The role requires advanced SQL and Python or R, causal inference expertise, scalable reporting, and the ability to communicate insights to senior marketing leaders.

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.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires independently structuring ambiguous problems, interpreting data, communicating persuasively with leadership, and delivering measurable business impact.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Analyzes healthcare claims, provider, reimbursement, and financial data to support out-of-network dispute negotiations, arbitration, QPA accuracy, and IDR performance. Builds SQL-based reports, dashboards, data processes, metrics, and financial views; validates data quality; integrates internal and external sources; identifies trends and risks; and presents actionable recommendations to leadership and cross-functional stakeholders.

Leads customer-facing healthcare analytics for medical claims, economics, health plan performance, and cost mitigation. Advises account teams and clients by translating complex data into strategic recommendations, oversees analytics priorities and resources, collaborates with clinical consultants, and supports retention and growth objectives. Requires strong healthcare industry knowledge, medical economics expertise, relationship management, communication, project management, and advanced analytical skills.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.