Top Financial Services Data Engineering Jobs in Chicago, IL

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

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

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

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.

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.

As the Senior Manager of Analytics Engineering, you'll lead a team to build data models, ensure data quality, and deliver impactful insights through analytics. You'll collaborate with various teams, utilize AI advancements, and drive decision-making by optimizing data solutions and tools.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

Responsible for implementing AI data pipelines, developing AI-driven systems, and ensuring the reliability and scalability of data solutions while mentoring junior team members and collaborating with cross-functional teams.

Analyze data to enhance trading strategies, build data pipelines, and collaborate with quant researchers and engineers to ensure data accuracy and availability.

The Quantitative Engineer Analyst will design and implement software components for data analysis and modeling, ensuring high-quality outputs and continuous improvement. They will collaborate with stakeholders, build big data pipelines, and produce documentation for models and tests.