Top Senior Analytics Jobs

Lead design and implementation of enterprise internal employee fraud detection rules and proactive monitoring. Use advanced analytics (SAS, SQL) to identify emerging threats, recommend rule enhancements, and partner with senior leaders, Risk, Compliance, and Technology to ensure effective, auditable controls and scalable detection solutions.

Lead strategy, design, and implementation of enterprise employee fraud detection rules. Use advanced SAS and SQL analytics to detect anomalous activity, drive proactive monitoring, partner with senior stakeholders, ensure governance and audit readiness, and provide thought leadership on fraud detection methodologies and controls.

Lead pricing analytics for GoodRx Companion subscription: build forecasting and elasticity models, optimize pricing to drive signups and unit economics, create dashboards and reports, analyze fill patterns, and deliver actionable insights to cross-functional stakeholders to improve program performance.

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.

Lead and scale a casino analytics team to drive data-informed strategy, experimentation, and reporting. Partner with product, data science, and operations to deliver executive insights, build analytical frameworks, and develop high-performing analysts to unlock growth and operational efficiency.

Lead analytical and strategic work across marketing, product and credit risk: identify opportunities, build models, support product/pricing strategy, enable direct-to-consumer marketing, drive execution and cross-functional implementation, and monitor outcomes to improve profitability and customer engagement.

Lead complex data analysis and modeling for private equity and corporate clients across the deal lifecycle. Deliver actionable insights using advanced analytics and visualization tools, improve data quality, collaborate with cross-functional teams, coach staff, and validate outcomes with clients to drive transaction and post-deal decisions.

Lead complex data analysis for private equity and corporate clients across the deal lifecycle. Translate data into actionable insights using analytics, visualization, and predictive modeling tools; drive data quality, collaborate with cross-functional teams, validate outcomes with clients, and coach teams to deliver strategic, data-driven solutions at deal speed.

Lead development, validation, and implementation of auto pricing loss estimation models. Drive complex analytics, translate model outputs into executive recommendations, monitor portfolio loss performance, and partner with Pricing, Risk, Finance, and regulators to optimize profitability and compliance.

Lead development, validation, and implementation of auto pricing loss assumptions. Drive complex analytical and modeling initiatives using large-scale data to inform pricing, credit loss forecasting, and portfolio profitability. Advise senior leadership, monitor portfolio performance, and collaborate with Pricing, Risk, Finance, and operations to ensure regulatory compliance and improve forecasting accuracy.

Lead strategy, development, validation, and implementation of auto pricing loss estimates. Build and enhance statistical models using large-scale data to inform pricing, portfolio profitability, and regulatory-compliant risk assumptions. Provide thought leadership to senior stakeholders, monitor portfolio loss performance, and translate complex analyses into actionable executive recommendations.

Lead strategy, development, validation, and implementation of loss estimation for auto pricing. Build and review complex statistical models using large-scale data to inform pricing, risk, and profitability. Advise senior leaders, monitor portfolio performance, ensure regulatory compliance, and translate analyses into actionable business recommendations.

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.

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.

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 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.

Perform advanced fraud risk analyses, develop and implement point-of-sale fraud strategies (rules, cutoffs, policies), identify key metrics, collaborate with cross-functional partners, and present findings to senior management to reduce fraud losses while minimizing customer impact.

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.