Top Fintech Data Science Jobs in Chicago, IL

Responsible for measuring servicing and risk metrics, leveraging analytics to enhance customer experience, mentoring junior members, and ensuring data-driven decision-making in a big data environment.

The Data Scientist will analyze data, develop algorithms, and utilize predictive modeling and machine learning to drive business decisions and insights.

The VP will lead the Claims Data Science organization, focusing on AI capabilities to enhance claims outcomes and customer experience. Responsibilities include overseeing the data science team, collaborating with business leaders, and managing AI strategy implementation.

The Principal Data Scientist designs and develops models to assess risk and prevent fraud, leads data scientists, and manages complex datasets while communicating findings to technical and non-technical audiences.

As a Quantitative Researcher, you will develop trading strategies using machine learning algorithms, enhance predictive models, and optimize workflows for efficient research.

The Senior Data Scientist will develop machine learning models, collaborate with cross-functional teams, and help improve credit risk assessments to drive business growth.

The Staff Data Scientist will develop machine learning models, collaborate with cross-functional teams, and use analytics to drive business growth and improve credit risk assessment.

As an AI-First Data Scientist, you will design and deploy ML solutions, conduct causal analysis, and automate intelligence in decision-making processes. You will work closely with senior operators and business leaders, translating complex problems into data-driven solutions while ensuring model performance and scalability.

The Senior Data Scientist will develop and implement ML models for financial data, translating business challenges into data science problems and owning the entire model lifecycle.

As a Data Science Intern, you will analyze data, create predictive models, and generate insights to support business decisions and program enhancements.

Support the data science team by analyzing data, executing SQL queries, validating results against analytics tools, and providing insights on user and product behavior.