Top Analytics Jobs

Lead enterprise data risk analytics by defining and standardizing metrics, building dashboards and data products, monitoring trends, and delivering actionable insights to executives. Translate data policies into measurement frameworks, automate metric processes with AI, lead cross-functional initiatives, and mentor junior analysts. The role requires substantial data analysis, programming, business intelligence, stakeholder influence, and strategic data management experience.

Analyze post-sales customer lifecycle data, including adoption, retention, renewals, churn, and expansion. Build Salesforce reports and dashboards, query and validate data with SQL, and create recurring analyses and visualizations using Excel, Tableau, and other BI tools. Partner with Customer Success, CS Operations, Analytics, BI, and Sales Systems teams to improve reporting, investigate trends, identify risks, and communicate actionable insights to technical and non-technical stakeholders.

Undergraduate interns will support data and analytics projects involving data pipelines, machine learning, generative AI, dashboards, reporting, data governance, process improvement, production support, and analytics solution development. Interns will collaborate cross-functionally, document data assets, validate data, and present project outcomes. The hybrid program requires approximately 40 hours weekly for ten weeks in Cary, North Carolina.

Co-op supporting supply chain analytics initiatives through data engineering pipelines, business dashboards, predictive analytics, and forecasting models. The role involves working with large datasets, translating business needs into Power BI dashboards and analytical models, and helping deliver projects that improve operational decision-making. Candidates should understand machine learning, forecasting, cloud technologies, SQL, Python, relational databases, and supply chain operations.

Analyzes sourcing, merchandising, financial, and vendor data to support negotiations, reporting, strategic planning, and KPI optimization across Ahold Delhaize USA brands. Develops project plans, reporting tools, negotiation insights, and process improvements; partners cross-functionally with sourcing and category teams. Uses DSS, Power BI, Circana, and Microsoft Office to identify savings, growth, and scale opportunities. Also trains team members and supports long-range planning, facilitation, and change management.

Owns A-Brands sourcing analytics, financial insights, reporting, and negotiation support. Builds data tools and fact packs, identifies savings and growth opportunities, supports strategic planning and RFPs, manages project deliverables, and partners cross-functionally with sourcing and merchandising teams. Uses DSS, Power BI, Circana, and Microsoft Office to analyze KPIs, improve processes, and inform CPG negotiations. Also trains associates, shares best practices, and serves as a subject matter expert for Center Store categories and vendors.

Owns analytics for digital marketing campaigns, including performance measurement, customer behavior analysis, A/B and incrementality testing, profitability analysis, and optimization. Translates large datasets into actionable recommendations for marketing partners and senior leaders through storytelling, presentations, and visualizations. Supports data-driven budget allocation, targeting, customer acquisition, and campaign strategy across digital channels.

Own end-to-end analytics for digital marketing campaigns, including customer behavior analysis, performance measurement, A/B and incrementality testing, profitability analysis, optimization, and budget allocation. Translate large datasets into executive-ready insights and recommendations through storytelling, presentations, and visualizations. Partner with marketing strategy leaders to improve campaigns, develop new approaches, and support customer acquisition and business outcomes.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

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.

Analyze and resolve pricing control exceptions involving fees, interest, refunds, and servicing activities. Review processes, build automated analytical workflows, develop reporting, and apply anomaly detection and responsible generative AI concepts. Partner with analysts, managers, product, operations, analytics, and technology teams to improve monitoring, documentation, and controls. Communicate findings clearly, manage multiple workstreams, and drive continuous improvement across card pricing operations.

Conduct quantitative research and pricing analytics for credit card installment products. Apply statistical modeling, econometrics, hypothesis testing, causal inference, and experimentation to evaluate pricing strategies, customer behavior, profitability, and policy effectiveness. Build scalable analytics processes, communicate insights to senior stakeholders, and partner with Finance and Marketing. Lead and develop analytics talent while evaluating responsible applications of artificial intelligence and automation.

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.

Lead digital marketing analytics strategy through quantitative research, experimentation, customer behavior analysis, and campaign measurement. Build and manage a high-performing analytics team, develop scalable processes, partner with Marketing, Finance, Product, and Technology, and translate complex findings into business actions. Apply statistical, causal, econometric, and experimental methods while evaluating responsible uses of AI and automation to improve marketing optimization and decision-making.

Lead end-to-end forecasting and offer analytics for the full credit card portfolio. Responsibilities include forecasting optimization, automation framework development, ad hoc analytics and reporting, generative AI applications, process improvement, controls management, compliance certifications, and senior leadership communication. The role partners closely with product, finance, risk, campaign management, marketing, and other cross-functional teams.

Designs and delivers data-driven audience, targeting, and measurement solutions for digital marketing campaigns. Translates business goals into technical requirements, improves data quality and reporting, standardizes audience documentation, and manages initiative execution, monitoring, issue triage, and alerts. Partners with Marketing, Product, and Technology on platform enhancements while identifying responsible artificial intelligence applications with human oversight, governance, explainability, and measurable outcomes.

Support digital product analytics for an application status platform by defining measurement strategies, KPIs, analytical frameworks, dashboards, governed datasets, and anomaly alerts. Analyze platform data, identify trends and performance issues, communicate recommendations to product and technology stakeholders, and collaborate on instrumentation and pipelines. Use AI-enabled tools to accelerate validated analysis while building reusable playbooks and scalable self-service reporting capabilities.

Develops automation, data pipelines, databases, analytics, machine learning models, reporting tools, and web applications for package technology quality assurance. Analyzes manufacturing, product, and reliability data to support risk assessment and root-cause investigations. Collaborates with engineering teams, communicates findings, trains users, maintains software and reports, and shares analytics best practices across global teams.

Supports Cencora’s enterprise data and analytics platform modernization by collecting and analyzing datasets, creating dashboards with BI tools, tracking KPIs, conducting ad hoc analyses, documenting findings, and contributing to CI/CD and self-service solution delivery. Collaborates with cross-functional stakeholders to provide actionable insights, improve processes, and support data-driven decisions for internal and customer-facing products.

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.

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 product analytics for Retail Bank growth, using SQL, Python, R, experimentation, causal inference, statistical modeling, segmentation, and data storytelling. Partners with Product, Engineering, Finance, and Research to shape roadmaps, prioritize opportunities, establish KPI standards, and influence investment and product decisions.