Top Financial Services Data Engineering Jobs in Chicago, IL

Lead the Emerging Fraud team as a Senior Data Scientist, developing machine learning models to identify and neutralize fraud threats, leveraging a wide range of technologies.

Collaborate with quant researchers to implement trading strategies, translate models into code, and optimize algorithms for execution.

The role involves architecting data models, ensuring data integrity, collaborating with teams on data strategies, and implementing innovative data solutions. Requires strong analytical skills and expertise in data management technologies.

Lead the Global Data Science & Analytics Product Development team, leveraging data science expertise to build market-leading data products and analytic solutions.

Lead a team to develop and maintain risk models, oversee model analytics, monitor performance, and collaborate with cross-functional teams. Utilize mathematical models and coding in R and Python for financial products.

The Senior Quantitative Analyst will define project objectives, manage projects, conduct data engineering, code, and ensure production compliance, while collaborating with stakeholders.

The Staff Data Engineer will define the technical strategy for enterprise data systems, build and optimize data pipelines, and provide architectural leadership while mentoring teams and ensuring data excellence.

The Senior Analytics Engineer will drive analytics projects, improve customer experiences, and develop self-service tools while collaborating with stakeholders to meet business needs.

The AI Underwriting Specialist will develop AI-driven underwriting processes, collaborate with various teams, and ensure compliance while improving efficiency and customer satisfaction.

The Quantitative Engineer Analyst assists in designing and implementing software components for data and analytics, collaborating with stakeholders and developing models and testing processes.