Top Hybrid Data Analysis Jobs

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.

Owns fraud and market-abuse detection models, rules, and partner-facing surveillance reporting across trading data. Investigates wash trading, collusion, hedging, reverse trading, and other suspicious activity; calibrates thresholds, validates false positives, maintains data quality, and produces evidence-based findings. Requires strong SQL, cloud data warehouse experience, futures and derivatives knowledge, anomaly detection expertise, and the ability to communicate findings to partners and executives.

Analyze Experian portfolio repayment performance, credit risk, underwriting and credit-limit changes, collections, funnel metrics, cohort LTV, and unit economics. Own partner analytics models, data definitions, reporting, alerting, and data quality monitoring. Collaborate with Product, Engineering, Partnerships, Finance, and Experian to guide roadmaps, evaluate experiments, identify risks, and support business reviews.

Build and lead Apptronik’s People Analytics function, developing workforce analytics strategy, predictive models, dashboards, KPI frameworks, and data governance. Advise executive leadership on talent strategy, organizational health, workforce planning, and organizational design. Establish people-data standards, security, access controls, compliance practices, and architecture in partnership with IT and Data Engineering. Translate workforce data into actionable business narratives while mentoring analytics teams and supporting HR initiatives.

Own the measurement framework for a marketplace product, including KPIs, dashboards, instrumentation, reporting, experimentation, statistical modeling, forecasting, and opportunity sizing. Analyze product engagement, conversion funnels, feature performance, and NPS drivers. Partner with Product, Marketing, Sales, and data teams to deliver actionable insights, improve analytics capabilities, and influence commercial and product decisions.

Analyze player behavior, product performance, revenue, retention, and engagement for Zynga Poker. Design experiments, dashboards, ETL pipelines, telemetry, fraud models, and business intelligence solutions. Partner with product, game design, economy, and consumer insights teams to guide decisions and improve player experiences. Contribute to AI-enabled analytics workflows, game integrity initiatives, and analytics best practices.

Lead end-to-end quantitative market research, including research planning, surveys, advanced statistical analysis, synthesis, and stakeholder presentations. Build and manage brand and sentiment measurement programs, identify customer and market trends, and provide strategic recommendations for growth and product opportunities. Partner with business leaders, promote research-driven decision-making, and mentor junior researchers while scaling the organization’s research practice.

Lead analytical projects and experiments focused on customer and product behavior, lifecycle growth, segmentation, and engagement. Build data models, semantic layers, AI agents, dashboards, and reporting systems. Partner with Product, Marketing, Engineering, and Data teams to define metrics, evaluate initiatives, and influence strategy. Apply statistical modeling, predictive analytics, causal inference, and experimentation techniques, while communicating actionable insights to technical teams and senior leadership.

Leads the commercial analytics function, developing advanced analytics frameworks, performance metrics, dashboards, forecasts, and strategic insights. Partners with senior leadership and cross-functional teams to optimize sales performance, resource allocation, commercial strategy, and operational efficiency. Oversees data quality, competitive analysis, sales compensation planning, analytical tools, and direct-report performance while promoting data-driven decision-making across the organization.

Analyze payment fraud data using SQL and dashboards, identify anomalous behavior and risk trends, evaluate fraud controls, and recommend improvements. Present findings to leadership and collaborate with Product, Data Science, Engineering, Customer Experience, and Risk Analytics teams. The intern will also document risk processes and responsibly use generative AI to improve workflow efficiency and quality.