Top 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 advanced analytics and measurement initiatives supporting HR, talent, culture, employee experience, and organizational health decisions. Partners with executives to frame complex questions, develop statistical methodologies, synthesize data, establish evaluation frameworks, and communicate actionable recommendations. Manages cross-functional projects, influences stakeholders, applies emerging analytics technologies, and mentors analysts.

Lead analytics workstreams for health plan clients: define problems, analyze data, build models and dashboards, synthesize insights into strategic recommendations, manage client relationships, and collaborate with teams to deliver actionable solutions.

Design and apply advanced statistical models and custom analyses (R, SAS, Tableau, VB, Excel) to inform client decisions, communicate results, build client relationships, produce deliverables, mentor junior team members, and support project status and implementation.

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.

Analyze Talent Acquisition and people data to identify hiring trends, bottlenecks, quality issues, and equity opportunities. Partner with recruiting and business leaders to translate ambiguous questions into rigorous analyses, validate data, monitor metrics, and deliver actionable recommendations. Lead analytics projects end to end while using storytelling, product management, design thinking, and data-driven iteration to improve employee and candidate experiences.

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.

Inovalon seeks candidates to join their Talent Community, emphasizing data-driven solutions to enhance healthcare outcomes and economics.

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.

Uses consumer, shopper, market, and retail analytics alongside qualitative research to uncover insights, inform business strategy, evaluate advertising and promotional investments, and influence product, pricing, media, retail, and go-to-market decisions. Partners cross-functionally with Brand Management, Finance, Sales, R&D, and other teams to communicate findings, identify growth opportunities, and drive action.

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.

Analyze and maintain investment data, build quantitative models and performance attribution systems, automate reporting workflows, and create dashboards for investment teams. Partner with research, portfolio construction, risk, and technology stakeholders to translate business needs into reliable data solutions. Support data quality, model governance, backtesting, scenario analysis, factor research, process improvement, and evaluation of AI and machine learning capabilities.

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.

Lead data-driven initiatives by partnering with marketing, product, and BD to inform acquisition and partnership strategies. Design, run, and analyze A/B experiments, leverage machine learning for in-depth analyses, test growth levers, and automate manual processes to improve operational efficiency.

Partner with cross-functional teams to drive data-driven growth: design and analyze A/B tests, leverage machine learning for insights, define acquisition and partnership levers, and automate processes to improve operational efficiency.

Partner with marketing, product, and biz-dev to drive data-driven growth. Design, run, and analyze A/B tests, define acquisition and partnership levers, leverage machine learning for insights, and automate operational processes to improve efficiency and scalability.

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.

Develop and productionize underwriting analytics, predictive models, and decision tools using statistical and machine learning techniques. Partner with underwriting, broking, actuarial, and portfolio teams to perform feature engineering, exploratory analysis, model validation, visualization, and monitoring to support risk segmentation, portfolio insights, and underwriting optimization.

Develop and productionize analytical models and data products to support underwriting and portfolio management. Apply statistical and machine learning methods to insurance datasets, perform exploratory analysis, feature engineering, validation, and create visualizations and presentations for technical and business stakeholders. Partner with underwriting, broking, actuarial, and portfolio teams to deliver scalable underwriting analytics and monitoring solutions.

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.

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.

Support regulatory reporting by analyzing trade and customer account data, responding to regulator and customer inquiries, identifying data anomalies, improving reporting processes, implementing AI/ML automation, and ensuring data governance, quality control, and acceptance testing for reporting systems.