Top Analytics Jobs

Leads AI-enabled pricing and commercial excellence initiatives for John Deere Construction & Forestry. Applies analytics, competitive intelligence, pricing models, and scalable processes to improve deal quality, decision speed, revenue, and margins. Partners with pricing, sales, marketing, finance, revenue management, dealers, and leadership to translate complex data into actionable guidance and drive adoption of advanced pricing capabilities.

Participate in a three-year rotational development program across John Deere business areas. Apply data science, data engineering, statistical analysis, predictive modeling, visualization, and programming techniques to solve business problems. Manage large datasets, support analytics projects, collaborate with stakeholders, and build expertise in analytics technologies while completing three one-year assignments.

Analyze AML investigation volumes, risks, productivity, capacity, KPIs, and financial contributions. Develop analytical recommendations, optimize investigative operations, support modeling and strategy, and lead implementation and monitoring efforts. Partner with IT, Sales, Operations, Finance, and other teams to improve quality, service, volume, and profitability while supporting AML defenses and law-enforcement investigations.

Develop and deploy analytical and AI-enabled tools integrated with the Aladdin platform to support portfolio construction, investment research, relative value analysis, risk budgeting, due diligence, and portfolio monitoring. Partner with portfolio managers and engineering teams to identify opportunities, prototype solutions, manage delivery, and productionize scalable applications. Communicate insights clearly while applying knowledge of financial markets, asset classes, Python, SQL, and modern technology stacks.

Conduct forward-looking index projections, research corporate actions and rebalances, analyze benchmarks, and apply quantitative and data science techniques to financial data. Build index research analytics capabilities, develop risk controls, collaborate with portfolio management and quantitative research teams, and provide data-driven insights supporting investment decisions, index strategies, products, and clients.

Leads complex business analyses for Engineering, building financial and operational models, datasets, metrics, dashboards, and executive decision materials. Identifies efficiency and cost-saving opportunities, designs resource-allocation frameworks, manages recurring planning and reporting, and coordinates cross-functional initiatives across Engineering, Product, Modeling, Finance, and Corporate teams.

Own product analytics strategy for a retail banking product, influencing roadmap and investment decisions through experimentation, causal inference, statistical modeling, and KPI frameworks. Query and transform large datasets using SQL, Python, or R; design and analyze A/B tests; identify growth opportunities; and communicate actionable insights to Product, Engineering, Finance, Research, and executive stakeholders.

Leads a team of approximately six analysts responsible for customer loyalty and experience analytics across banking businesses. Oversees satisfaction, NPS, survey, behavioral, operational, and financial analysis; translates findings into executive recommendations; quantifies business impact; advances AI and analytical innovation; supports executive, board, and regulatory reporting; and establishes consistent enterprise customer measurement practices.

Leads a data analytics team comprising data scientists, BI analysts, and AI developers. Provides mentorship, technical oversight, workflow optimization, performance management, stakeholder communication, project prioritization, and governance stewardship. Ensures analytical integrity, data quality, privacy, AI validation, ethical practices, and alignment with organizational goals. Partners with data engineering and executives to translate business needs into technical objectives and actionable insights.

Analyzes complex small-business card portfolio and customer behavior data to generate insights for marketing, finance, product, and risk decisions. Builds executive reporting and dashboards, applies statistical and data-mining methods, advises stakeholders, improves data quality and analytics processes, and pilots generative AI solutions to automate workflows and enhance performance measurement.

Develop fraud risk strategies and analytical solutions using complex datasets, SAS, SQL, Python, and machine learning. Monitor fraudulent behaviors, create risk metrics and dashboards, design loss-mitigation products, and present recommendations to senior stakeholders. Manage strategic initiatives, collaborate with product and operations teams, and supervise analytics employees through delegation, performance management, hiring, and mentorship.

Leads quantitative and qualitative Medicaid policy research from project scoping through dissemination. Oversees data acquisition and analysis, monitors state and federal policy changes, develops briefs and presentations, conducts stakeholder interviews, supervises research staff, manages external collaborators, and translates findings into actionable recommendations for policymakers, providers, advocates, and the public.

Analyze branded credit card business performance, P&L initiatives, customer and product strategies, marketing outcomes, credit risk, and operational efficiency. Build queries, models, and dashboards; develop business cases; monitor post-launch results and risks; and translate complex data into actionable recommendations. Collaborate with marketing, finance, risk, product, technology, analytics, and operations stakeholders to drive growth and measurable business outcomes.

Analyzes branded credit card product and customer performance, develops P&L initiatives and business cases, builds data models, queries, and dashboards, evaluates marketing, credit risk, and operational impacts, monitors post-launch results, identifies risks and growth opportunities, and presents data-driven recommendations. Partners cross-functionally with marketing, finance, risk, product, technology, analytics, and operations teams to support strategic business decisions.

Analyze credit card business performance, customer and product trends, marketing outcomes, risk, and operational efficiency. Build queries, models, and dashboards; evaluate P&L initiatives and business cases; identify risks and growth opportunities; and translate insights into actionable strategies. The role partners with marketing, finance, analytics, risk, product, technology, and operations stakeholders to support strategic decisions and measurable business outcomes.

Own commercial analytics for direct-to-consumer and marketplace channels, analyzing pricing, promotions, conversion funnels, merchandising, product mix, customer behavior, and channel economics. Build scalable reporting tools, support forecasting and planning, and translate transactional and behavioral data into recommendations for digital commerce leadership. Partner with Marketing Analytics and Analytics Engineering to connect acquisition trends with commercial outcomes and ensure trusted data.

Maintains and analyzes investment data for clients by organizing raw data, building data systems and pipelines, integrating multiple sources, and improving data quality. Develops analytical tools, performs data mining, creates visualizations and reports, and collaborates with architects, product teams, clients, and project managers to meet business requirements.

Executes quantitative analytics for cobrand credit card portfolios, focusing on acquisition, engagement, retention, attrition, rewards, and cardholder value. Develops analytical frameworks, supports experimental design, maintains data integrity, applies segmentation and generative AI, and presents actionable recommendations to senior leaders and partners. Collaborates with marketing, product, and analytics teams to improve partnership strategy and customer outcomes.

Own product analytics for embedded business areas, leading experimentation, root-cause analysis, business-case development, KPI reporting, and strategic recommendations. Build dashboards and Looker explores, partner with engineering teams to improve data models and reliability, present insights to leadership, use AI tools to improve analytics efficiency, and mentor analysts. The role requires advanced SQL, Python, statistical experimentation expertise, and experience with consumer fintech or similar B2C data.

Leads and scales Hi Marley’s analytics function, managing analysts and hiring as the team grows. Establishes trusted company metrics, self-service analytics, standards, and an analytics roadmap. Partners with Product, Customer Success, Growth, Marketing, Finance, and Data Engineering on product, customer, revenue, financial, billing, marketing, experimentation, and utilization analysis. Develops people, communicates insights to executives, and drives data-informed decisions across the organization.

Leads an analytics team supporting Home Lending Operations by framing business problems, delivering analysis, building reporting, defining data requirements, and advising senior stakeholders. Develops AI and machine learning use cases to optimize operations and customer experiences, establishes analytics quality standards, supports experimentation and product measurement, and partners cross-functionally with Operations, Product, Technology, Finance, Strategy, Business Intelligence, and Modeling teams.

Manage data analytics for PULSE Risk & Compliance by analyzing large datasets, identifying transaction anomalies and risk exposure, validating models, improving reporting and processes, and supporting compliant data strategies. The role involves Python-based programming, BI, database and data-storage design, strategic testing, cross-functional collaboration, project leadership, and people management in a hybrid environment.

Analyze complex data to support business decisions, build self-service data solutions, develop dashboards and metrics, and improve data quality and governance. The role uses Python, R, Spark, SQL, AWS, business intelligence tools, and data management practices while partnering with business and technology teams on analytics and transformation initiatives.

Analyze go-to-market performance across Sales, Marketing, and Client Success, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and data marts using Salesforce and modern data-stack tools. Own data quality, documentation, BI-as-code contributions, and AI-enabled analytics workflows. Partner with stakeholders to turn ambiguous business questions into actionable recommendations and deliver results in agile two-week sprints.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.