Top Data & Analytics Jobs

Supports Customer Analytics initiatives by identifying opportunities for data, automation, and AI solutions; translating business needs into requirements; developing and testing prototypes; coordinating implementation; measuring solution impact; modernizing processes; and enabling self-service data capabilities. The role requires cross-functional stakeholder management, project delivery, data integrity controls, and communication with technical teams and senior business leaders.

Develops and maintains secure, scalable data pipelines and architectures using Python, Databricks, AWS, SQL, and NoSQL technologies. Responsibilities include ELT workflow development, data modeling, enterprise data security, controls validation, statistical analysis, and cloud application management. The role also requires using and validating AI-assisted development tools for code generation, testing, documentation, and pipeline design while maintaining auditability, resiliency, and data sensitivity standards.

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.

Develops and maintains Python data pipelines and business data objects. Designs software solutions, implements source-to-target mappings, builds CI/CD pipelines, and performs unit and integration testing. Resolves complex technical problems, interprets design requirements, and promotes software quality and team improvement. The role requires onsite work five days per week in Chicago, Peoria, or Dallas.

Leads product analytics and partners with product and executive leadership to guide strategy, roadmap prioritization, experimentation, and optimization. Translates customer and business questions into measurable outcomes, analytical roadmaps, segmentation, funnel and cohort analyses, and evidence-based recommendations. Owns product measurement frameworks, dashboards, data quality, instrumentation, and governance while communicating insights, trade-offs, and actions to senior stakeholders.

Lead the rebuild and modernization of the company’s data platform by designing and implementing an Azure and Databricks lakehouse. Responsibilities include managing Azure Data Factory pipelines, developing Delta Lake architectures, creating data models and transformations with SQL and Python, establishing development standards, monitoring data quality, troubleshooting performance issues, leading technical projects, and mentoring or hiring data engineering staff.

Develop data models, analyses, dashboards, and automated reporting for a collectibles marketplace. Partner with engineering, product, and data platform teams to define business metrics, identify customer experience and growth opportunities, inform strategy, and lead initiatives that improve business performance.

Lead consumer lending analytics and strategy across credit card, HELOC, and Auto/RV products. Evaluate portfolio performance, member behavior, pricing, targeting, risk, profitability, and growth opportunities. Develop strategic recommendations, forecasts, business cases, and analytical frameworks using SQL and large datasets. Partner with finance, credit risk, marketing, operations, and technology leaders while managing, coaching, and developing an analytics team.

Own marketing measurement from initial engagement through closed-won revenue. Manage cross-channel reporting tied to Salesforce pipeline, tracking across GA4, advertising platforms, SEO, and AI search. Validate multi-touch attribution, analyze marketing experiments, model budget impact, and recommend investment priorities. Present performance insights to marketing and sales leadership across global regions.

The Lead Data Migration Specialist will enhance data processes for client onboarding using Excel, SQL, and AI, ensuring accuracy and efficiency.

The Senior Data Scientist will lead analytics projects, define success metrics, run experiments, and present data-driven insights to influence product and business strategies.

Leads enterprise data architecture initiatives by translating business requirements into scalable data designs, assessing impacts across systems and pipelines, modernizing legacy environments, and guiding AI/ML data solutions. Partners with data leaders and stakeholders, manages project plans, monitors implementation progress, and communicates risks and mitigation plans. Requires expertise in cloud and hybrid environments, data platforms, data engineering or architecture, and team or project management.