Top Tech Jobs & Startup Jobs in Chicago, IL

Design, develop, and deploy supervised machine learning models for credit decisioning. Collaborate with business and technical stakeholders to create data sources, improve modeling methodology, operationalize models, and manage model evaluation and risk for production systems.

Build and maintain advanced financial models and tools to evaluate funding alternatives, structure debt and equity strategies, and support capital raise activities. Partner with Credit, Data, and FP&A teams, generate investor materials, present to investors and senior management, and leverage large datasets and AI to drive reporting, analytics, and execution across the capital stack.

Lead Mission Lane's first-line operations risk function: build the team, define first- vs second-line accountability, partner with process owners to design controls, manage incident lifecycle, deliver executive risk reporting, and coordinate remediation with Legal, Risk, and Compliance.

Lead content strategy and infrastructure to drive SEO, AI-search, and owned-channel performance. Build multisource content models, governance, PR/citation strategy, and content feeds for CX tools, ensuring compliance in a regulated fintech environment.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

The Principal Business Analyst will lead initiatives to optimize underwriting and acquisition strategies, leveraging data analysis and collaborating with cross-functional teams to improve profitability and credit risk.

Lead a data science team focused on credit risk modeling: design, develop, deploy, and manage production machine learning models. Partner cross-functionally to improve data sources, modeling methodology, risk management, and team capabilities.

Lead marketing operations for direct marketing campaigns in a regulated environment. Own process design, governance, digital asset management, QA/audit controls, vendor and team management, operational reporting, and identify automation opportunities to improve cycle times and compliance while scaling from direct mail into digital channels.

Lead fraud analytics for application fraud detection: identify emerging patterns, design and test real-time defenses, balance risk and customer experience, build dashboards and metrics, and collaborate with Operations, Product, Data Science, and Engineering to reduce fraud losses and improve cardholder experience.

Lead Mission Lane's AI operations strategy end-to-end: identify high-impact AI use cases for contact center operations, build business cases, evaluate vendors, sequence and drive cross-functional execution, establish governance, and measure outcomes in cost, quality, and customer experience.