Top Data & Analytics Jobs in Chicago, IL

Lead data analytics for network and merchant compliance: design tests, build models and reporting, mine large datasets, improve data quality and processes, advise stakeholders on risk, and manage a team to implement compliance analytics solutions.

Lead analytics and modeling efforts for enterprise arbitration across inbound channels. Evaluate and improve models, build model roadmaps, advise lines of business on credit and operational impacts, support product, marketing, and credit-risk initiatives, and partner with IT, sales, operations, and finance to implement and monitor data-driven solutions.

The Business Director leads insights and analytics for Community Finance, driving innovation and strategic decision-making through data analysis and operational execution.

As a Data Scientist Manager in Card Payment Fraud Prevention, you will lead a team to build and deploy machine learning models to combat first-party fraud, enhance customer safety, and optimize fraud capture rates by leveraging big data and advanced statistical methods.

The Manager of Ontology and Data Modeling develops and maintains ontologies, collaborates across teams, supports semantic technology integration, and manages teams focused on data modeling to achieve enterprise initiatives.

The role involves driving strategy through data analytics, leading a team, implementing process improvements, and developing data models. Requires strong analytical, problem-solving, and leadership skills.

Lead a team of engineers to design and implement data solutions using cloud technologies, optimizing data pipelines and collaborating with Agile teams to deliver impactful data-driven products.

The Senior Business Analyst will analyze business challenges, model product strategies, support marketing efforts, and enhance credit risk through strategic recommendations and analytics, collaborating across departments.

Lead data strategy and analytics for consumer products, mentor junior analysts, manage projects, and improve operational efficiencies using data-driven insights.

The role involves leading a team to develop machine learning models, analyze large datasets, and translate complex data insights into business goals. Requires collaboration with cross-functional teams to enhance decision-making and model validation.