Top Senior Analytics Jobs

Drive people strategy analytics: analyze historical data and benchmarks, build statistical models, support product/marketing/credit risk decisions, partner cross-functionally, implement analytically driven solutions, and communicate data-driven stories to senior leaders.

Lead design, validation, and monitoring of fraud strategies using data analysis and AI/ML. Partner with product, technology, and operations to develop detection capabilities, test implementations, and balance fraud mitigation with revenue, cost, and customer impact.

The Sr Manager of Payor Performance Analytics drives financial, analytical, and operational components of payer contracting, overseeing reimbursement modeling and ensuring successful contract negotiations and implementation.

Perform advanced quantitative analyses on large card portfolio datasets to inform marketing, product, finance, and risk decisions. Build executive dashboards and reports, apply data mining and statistical techniques, translate customer behavior into actionable insights, partner with stakeholders to optimize campaigns and portfolio profitability, and contribute to analytics architecture and process improvements with limited oversight.

Support home lending risk strategy by performing data-driven analyses, identifying trends, monitoring emerging housing and regulatory risks, and delivering clear recommendations and visualizations. Partner with Risk Policy, Product Strategy, and cross-functional teams to design risk segmentation, controls, and performance monitoring to align growth with the firms risk appetite.

Lead end-to-end quantitative research and segmentation studies using SQL, Python, and statistical methods. Analyze large datasets and surveys, synthesize findings into executive-quality insights, drive process improvements, mentor junior staff, and partner with product and senior stakeholders to integrate research into product development.

Lead analytics for card acquisition risk: collect and analyze internal/external data, develop strategies and controls, partner cross-functionally, present recommendations, and ensure regulatory compliance to drive financial performance and loss mitigation.

Perform end-to-end quantitative analytics for deposit pricing, focusing on CDs and elasticity testing. Analyze large money-movement datasets to inform pricing strategy, build automated interactive dashboards, ensure data accuracy, monitor competitor and macro trends, and present insights to senior leadership while partnering with pricing, finance, risk, marketing, and product teams.

Perform quantitative analyses of business lending portfolios to generate strategy recommendations, monitor portfolio and collection performance, design and test risk/growth strategies, produce periodic reporting, support ad hoc requests, and maintain audit‑ready documentation and controls.

Design and implement forecasting and automation solutions for finance. Translate business requirements into development-ready artifacts, collaborate with stakeholders and engineering, monitor solution performance, and document progress in JIRA.

Support collections and recovery by building predictive models and analytics, monitoring trends, and translating insights into operational strategies. Collaborate cross-functionally to design, test, and implement data-driven solutions, present findings using visualizations and narratives, and act as a subject-matter expert to optimize performance and manage expenses.

Perform quantitative analyses of business lending portfolios to inform strategy across acquisition, underwriting, portfolio management, collections and recoveries. Develop reporting, test pre/post-implementation impacts, produce actionable recommendations balancing growth and credit risk, and maintain audit-ready controls and documentation.

Develop, validate, and govern multi-year forecasting models estimating credit card customer engagement and balances. Produce incremental impact analyses using control groups, step-up factors, and performance monitoring; provide inputs to Finance for NPV/PTI, ensure model governance, documentation, and cross-functional alignment with Risk and Finance.

Volunteer lead responsible for managing a team of volunteer data analysts, overseeing precinct-level voter file and turnout data cleaning and analysis, producing standardized precinct reports and strategic recommendations for PCOs, maintaining project tracking systems, and ensuring data security while supporting voter engagement and GOTV strategies.

Support analytics initiatives by gathering, cleaning, modeling, and analyzing data. Produce forecasts, reports, and visualizations, document data and processes, and present actionable insights to influence leadership decisions while improving data quality and management.

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.

Lead AML/OFAC data analytics: collect, clean, and validate data; build models and dashboards; support model governance, validation, monitoring optimization, reporting, and remediation for BSA/OFAC programs.

Provide quantitative analytics and reporting for private credit portfolios (Direct Lending, Asset-Based Finance, Structured Credit). Build and automate models, dashboards, and data workflows; validate and reconcile investment data; support underwriting, portfolio monitoring, risk oversight, and senior reporting; collaborate with investment, risk, finance, operations, and technology teams.

Support US Options pricing and strategy through data analytics, statistical modeling, dashboarding, and forecasting. Evaluate client trading patterns, monitor competitive and regulatory developments, manage pricing change processes, and provide actionable insights to Sales and senior stakeholders across Derivatives and Futures.

Lead product analytics for Guest or Host App: analyze large datasets, design and evaluate experiments, build metrics and reporting tools, apply statistical and causal methods, partner cross-functionally, present insights to stakeholders, and leverage AI to automate tasks.

Lead a team of data analysts to analyze complex datasets, build models and forecasts, ensure data quality, and present insights to influence business strategy and drive growth across cross-functional stakeholders.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Develop and execute quantitative models and analytical methods to assess credit risk for Single Family mortgage products (modification, short sale, foreclosure, distressed valuation). Independently design, implement, and validate predictive models, support business and risk decisions, perform data cleaning and processing, and collaborate with stakeholders to provide practical, innovative solutions.

Develop, implement, and maintain counterparty credit risk models (PD/LGD/EAD). Collaborate with credit risk teams, run performance monitoring, address model review findings, ensure model governance compliance, and support validation, audit, and regulatory requests. Apply econometric and predictive modeling techniques to large datasets using statistical programming.

Design, validate, and deploy advanced quantitative models and predictive analytics to improve efficiency, reduce costs, and increase revenue. Collaborate with business partners to gather requirements, perform big data analysis, run simulations, and produce reports. Support model verification/validation and deployment.