Top Senior Analytics Jobs

Analyze complex marketing and customer datasets to produce actionable insights, executive dashboards, recurring reports, and campaign performance analyses. Define metrics, evaluate trends, communicate findings to senior leaders, and partner cross-functionally to support growth and improve marketing outcomes. Independently manage analytical workstreams, optimize processes, and develop data products incorporating artificial intelligence and large language models.

Analyzes customer and platform performance data, develops executive dashboards and scorecards, conducts root-cause investigations, and delivers actionable insights to clients and internal stakeholders. Partners with Customer Success, Product, Engineering, and Business Intelligence teams to improve reporting, standardize analytics, support forecasting, and inform strategic decisions. The role includes client-facing business reviews and periodic travel.

Leads development, validation, implementation, and monitoring of credit scorecards, loss forecasting, collection, recovery, and pricing models for auto lending. Provides strategic recommendations balancing growth, profitability, risk, and regulatory compliance. Partners with Pricing, Risk, Finance, and senior leadership, translating complex statistical analyses into actionable business insights. Uses large-scale data and advanced analytics to monitor portfolio performance, identify risks, and improve forecasting accuracy.

Performs moderately complex analytics, reporting, and data research supporting Financial Crimes Operations. Analyzes business, operational, and technical challenges; extracts insights from complex data environments; develops metrics and visualizations; supports strategic initiatives; and identifies engineering enhancements. Leads cross-functional projects, mentors staff, manages work independently, and applies compliance and risk-management requirements.

Leads development, validation, implementation, and monitoring of credit scorecards, loss forecasting, collection, recovery, and auto pricing models. Provides strategic recommendations balancing profitability, growth, risk, and regulatory compliance. Partners with Pricing, Risk, Finance, and Auto Lending teams, analyzes large-scale datasets, monitors portfolio performance, and translates advanced statistical analyses into executive-level insights using SAS, Python, Tableau, and Power BI.

Performs moderately complex data analysis, reporting, and business consulting for Financial Crimes Operations. Extracts insights from technical systems and business processes, supports strategic initiatives, identifies engineering enhancements, leads cross-group projects, mentors staff, and applies compliance and risk management knowledge. Develops metrics, visualizations, and analytical reports using large datasets while independently managing priorities and work requests.

Supports credit risk valuation and decision science for consumer lending portfolios. Maintains and deploys financial valuation models, performs quarterly FAS107 asset valuation, analyzes forecasting and reporting data, reconciles production outputs, documents governed models, and resolves modeling issues. The role applies credit card strategy, P&L modeling, statistical analysis, and portfolio analytics while leading initiatives, mentoring staff, and communicating insights to senior stakeholders.

Leads credit card acquisition analytics for U.S. consumer and small business portfolios. Manages data scientists and analysts, develops predictive models, evaluates marketing campaigns, shapes offer and targeting strategies, and translates customer and channel insights into measurable business outcomes. Partners with product and marketing leaders, communicates findings to senior stakeholders, and promotes experimentation, model governance, scalable reporting, and continuous improvement.

Leads digital marketing analytics strategy through quantitative research, experimentation, causal measurement, and customer behavior analysis. Partners with Marketing, Finance, Product, and Technology to convert insights into business actions. Builds and manages a high-performing analytics team, establishes scalable processes, evaluates AI-enabled workflows, and optimizes marketing performance through statistical methods, A/B testing, multivariate experiments, and profit-and-loss analysis.

Lead product analytics for Enterprise Data products, validating analytical tools, assessing methodology risks, researching emerging practices, and translating complex data into actionable insights. Manage validation projects, communicate findings through reports and presentations, and coach junior staff. The role requires advanced data analysis, statistical or econometric modeling, predictive analytics, large-dataset analysis, data governance, and people leadership.

Develop, implement, monitor, and enhance credit risk models using statistical, econometric, and machine learning methods. Analyze large datasets with Python, SQL, SAS, R, and Spark; perform forecasting, stress testing, feature engineering, and model validation. Document methodologies, support governance and regulatory reviews, communicate findings to stakeholders, and improve analytical automation and reporting processes.

Develop, implement, monitor, and enhance credit risk models using statistical, econometric, and machine learning methods. Analyze large datasets with Python, SQL, SAS, R, and Spark to support risk measurement, forecasting, stress testing, and portfolio management. Document methodologies, support validation and audits, address regulatory findings, and communicate model results to technical and executive stakeholders while following model governance requirements.

Develops and monitors credit risk models using statistical, econometric, and machine learning methods. Performs advanced coding, data analysis, feature engineering, forecasting, stress testing, and portfolio risk analysis using large datasets. Documents methodologies and governance processes, supports validation, audits, and regulatory examinations, and communicates findings to technical and executive stakeholders. Partners cross-functionally to improve analytical processes, automation, and model performance.

Leads business analysis and contact interaction analytics to deliver insights, dashboards, reporting solutions, modeling, and data-driven recommendations. Partners with marketing, product, platform, and cross-functional teams to define success metrics, optimize customer experiences, prioritize resources, and support strategic and operational decisions. Administers standardized reporting structures and self-service analytics environments while communicating complex findings to leaders across the organization.

Analyze customer behavior across digital and phone journeys, develop experiments and OKRs, and translate data into actionable recommendations. Partner with product, technology, design, modeling, and analytics teams to improve customer experiences and operational efficiency. Present insights to senior stakeholders, support predictive analytics and machine learning initiatives, and maintain data governance through collaboration with data owners.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Leads people analytics initiatives that support talent strategy and workforce decisions. Responsibilities include developing analytics frameworks, managing data projects, building AI-powered data products and self-service tools, analyzing workforce data, prototyping automation solutions, and delivering insights to HR stakeholders and senior leaders. The role also involves data strategy, dashboard development, project execution, and potentially people management.

Lead analytics for a corporate real estate portfolio, integrating financial, headcount, occupancy, and property data. Build scenario and financial models for capital allocation, expense planning, and portfolio strategy. Conduct ad hoc analyses, improve data workflows and data quality, and translate complex findings into concise executive presentations and strategic recommendations for senior leadership.

Leads commercial analytics across digital commerce, apparel and accessories, and wholesale. Manages analysts, owns bookings forecasting, develops customer and channel economics frameworks, and builds scenario-planning and measurement models. Partners with Finance and senior stakeholders to evaluate growth opportunities, diagnose performance, quantify tradeoffs, and guide investment decisions. Requires strong SQL, analytical modeling, people leadership, and cross-functional business judgment.

Designs and enhances fraud strategies using data analysis, advanced analytics, and AI/machine learning. Monitors fraud trends and customer friction, identifies root causes, and develops solutions that balance fraud mitigation, financial performance, customer experience, and operational efficiency. Partners with Product, Technology, and Operations to define requirements, implement capabilities, and validate results. Requires strategic planning, roadmap development, project management, compliance collaboration, and strong stakeholder communication.

Lead analytics for small business insurance marketing by developing audience segments, targeting strategies, campaign measurement, and experimentation plans. Partner with marketing, insurance, analytics, and technology teams to align data definitions, build scalable data assets, diagnose analytical issues, and deliver executive-ready insights. Use Python, SQL, cloud platforms, and modern data warehousing to improve campaign performance, conversion, incrementality, and decision-making.

Leads enterprise data risk measurement and analytics by defining metrics, building dashboards and data products, monitoring trends, translating policies into actionable insights, and presenting recommendations to executives. Manages junior analysts, drives cross-functional initiatives, supports data governance, applies AI to automate metrics, and performs analysis across large databases to improve processes, reporting, and business outcomes.

Leads the technical vision, architecture, and delivery of enterprise search analytics and ontology solutions for ecommerce. Manages and mentors software engineering teams, integrates platforms, oversees IT service operations and quality, and improves search relevance using NLP, vector search, personalization, machine learning, and performance KPIs. Partners with product, data science, and engineering leaders while driving ontology, metadata, governance, and semantic search adoption across digital commerce.

Develops fraud rules, models, dashboards, and strategies to reduce fraud losses. Analyzes emerging fraud trends, monitors KPIs, conducts ad hoc analysis, supports production deployments, and communicates findings to technical and business stakeholders. The Thursday-through-Monday schedule requires weekend availability, with a hybrid arrangement based in Chicago.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.