Top Senior Analytics Jobs

Own marketing analytics, attribution modeling, full-funnel measurement, forecasting, experimentation, and ROI optimization across campaigns, partners, and field marketing. Build Tableau dashboards, ensure martech data quality, implement AI/ML predictive capabilities, and translate complex data into strategic recommendations for marketing leadership. Partner cross-functionally on performance narratives, QBRs, and budget planning while mentoring junior analysts and establishing analytics best practices.

Leads advanced Revenue Growth Management analytics, complex business problem solving, next-generation capability development, AI use-case implementation, strategic projects, and organizational training. Partners with Advanced Analytics and Data Science teams to build scalable tools, translate RGM methodologies into solutions, and generate actionable insights across brand, trade, pricing, and commercial initiatives. Manages three direct reports and supports enterprise-wide analytical capability building.

Supports Revenue Growth Management through ad hoc analysis, pricing and promotion projects, analytical tool development, and maintenance. Builds Excel and Power BI capabilities, contributes to Next Gen RGM solutions, and supports AI integration into business processes. Partners with brand and commercial teams to generate actionable insights, improve efficiency, and inform strategic decisions.

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.

Own supplier-side pricing, yield, monetization, retention, and churn analytics for a B2B marketplace. Build scoring models, predictive machine learning models, dashboards, category and keyword data models, cohort analyses, and A/B tests. Partner with general management, product, operations, engineering, sales, finance, and customer success to translate marketplace insights into pricing, revenue, retention, and supplier engagement decisions.

Leads analytics teams delivering digital media measurement, testing strategies, campaign analysis, dashboards, and actionable insights for client accounts. Develops cross-channel measurement frameworks, evaluates marketing performance against KPIs and ROI, communicates findings to clients and stakeholders, and recommends investment and strategy optimizations. The role also develops analytics talent and ensures analytics integration across agency production processes.

Lead end-to-end research and production pipelines for systematic trading strategies. Conduct alpha research using statistical and ML techniques on high-frequency tick and order-book data, build Monte Carlo simulations and real-time risk monitoring, design position-sizing and stress-testing frameworks, mentor junior researchers, and collaborate with trading and infrastructure teams to deploy production-grade models and risk controls.

Lead prospect development and analytics for fundraising: design prospect scoring and predictive models, manage portfolios and pipeline, provide research and data-driven guidance to fundraisers, oversee CRM data integrity and a small team to optimize major gift strategies.

The Senior Data Scientist will analyze product data, design and manage experiments, define KPIs, and collaborate with cross-functional teams to improve product performance and user experience.

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.

Analyze audience impressions and research to create compelling sales presentations, guide promotions, and support newsroom viewership analysis. Provide research-driven strategic guidance across sales, programming, and creative teams using Nielsen and other media tools.

Design, test and implement consumer credit underwriting and pricing strategies using historical data. Extract and analyze data, build regression and machine learning models, employ decision-tree tools, optimize strategies across the credit lifecycle, ensure data quality, automate reporting, and present insights to management.

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.

Use data analytics to identify and reduce operational risk across EP & TBM. Analyze large datasets, perform root cause analysis, recommend scalable process improvements, build dashboards and visualizations, measure initiative effectiveness, automate reporting, and partner with engineering, product, and risk teams to prioritize and implement risk reduction.

Lead pricing strategy and origination risk analytics to optimize loan pricing, forecasting, and approval frameworks. Manage and mentor analysts, build quantitative models, integrate third-party data, run experiments, and present recommendations to senior leadership to drive growth and profitability.

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.

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.

Lead Compliance Data Analytics to research and analyze risk patterns (fraud, account takeover, payment fraud), deploy and iterate rules/models, partner with stakeholders to balance user experience and risk mitigation, drive business-centric analytics and strategic metrics, and build and manage a high-performing compliance analytics team.

The Staff Data Scientist will work with product teams to analyze data, identify improvement opportunities, design experiments, and create reporting dashboards to enhance contract management workflows.

Conduct enterprise-wide data analysis, manage large data sets, develop insights and dashboards, and prepare reports for stakeholders in support of decision-making.

Write complex SQL queries and manipulate large datasets to produce end-to-end financial analysis of domestic and global roaming traffic. Gather requirements, identify data sources, rationalize results, produce written analysis, troubleshoot queries, and collaborate cross-functionally to make recommendations and support reporting needs.