Top Data & Analytics Jobs

The Independent Assessment and Review Analyst will conduct fraud program assessments, evaluate effectiveness, and ensure compliance with standards while offering strategic insights and recommendations.

The Pricing Analyst will optimize mortgage pricing strategies to improve profitability, analyze data, collaborate with business leaders, and ensure pricing accuracy.

The Staff Risk Analyst will lead data governance initiatives, analytics, and reporting to improve fraud risk oversight and operational effectiveness, collaborating with cross-functional teams and ensuring data integrity across fraud metrics.

Lead subscription analytics for SoFi Plus: define engagement/retention metrics, run deep-dive analyses and experiments, build scalable data pipelines and ML models, create executive dashboards, and influence product strategy to grow subscription value.

Lead and grow a data science team to optimize lending funnels, run experimentation and statistical analyses, build reports/dashboards and data marts, partner with Product/Engineering/Finance, and translate insights to senior leadership to inform product decisions.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

The Analyst will conduct data analysis for operational efficiency, support modeling, ensure data integrity, and collaborate cross-functionally to improve performance metrics.

The Credit Bureau Business Analyst will manage bureau relationships, analyze credit data, influence strategies, and improve outcomes collaboratively across teams.

The Senior Risk Analyst will monitor fraud risk metrics, analyze fraud performance, and support governance and regulatory compliance within the Fraud Program. Responsibilities include metrics monitoring, data-driven reporting, and collaboration across teams to enhance fraud risk management.

The Staff Data Engineer will design and develop data models and pipelines, optimize data engineering processes, and enforce data governance, collaborating with cross-functional teams to meet business needs.