Top Tech Jobs & Startup Jobs in Chicago, IL

Leads data science and model risk oversight for credit card underwriting models. Builds, evaluates, validates, monitors, and implements machine learning models using large-scale structured and textual data. Partners with data scientists, engineers, and product managers to translate complex statistical findings into business outcomes, ensure effective model governance, and identify emerging technologies and analytical methods.

Develops deal economics, pricing, and analytics for Capital One’s Global Payment Networks. The role supports strategic negotiations, evaluates business opportunities, builds quantitative recommendations, and partners with Pricing, Corporate Development, Sales, and other teams to improve profitability and performance. Responsibilities include strategic analysis, statistical modeling, market research, stakeholder alignment, and driving outcomes across complex network relationships.

Leads data scientists, business analysts, and data analysts in developing machine learning models from design through implementation. Partners with software engineering and product teams to deliver customer-focused products, using Python, cloud computing, Spark, H2O, and other technologies to analyze large-scale numeric and textual data. Translates complex technical findings into business goals while developing team talent and evaluating emerging methods.

Leads data science for foundational AI and automation across a global payments network. Partners with data scientists, engineers, ML engineers, and product managers to develop scalable models and AI agents using PyTorch, AWS, vector databases, and LLMs. Serves as an NLP and LLM domain expert, translates technical work into business value, develops talent, and delivers production-scale libraries, platforms, and solutions.

Leads software engineering projects and developers building cloud-based, full-stack, distributed microservices and decisioning systems for Capital One’s Card Technology organization. Responsibilities include technical leadership, architecture and service design, mentoring, cloud development, performance optimization, refactoring, regulatory solutions, and establishing engineering standards across Agile teams.

Leads data science initiatives using machine learning, statistical modeling, and large-scale data analysis. Partners with software engineers and product managers to develop customer-focused products, builds and validates models across the full development lifecycle, translates technical findings into business outcomes, evaluates emerging technologies, and develops data science talent. Requires substantial experience with programming, machine learning, relational databases, cloud computing, and people management.

Leads data science and machine learning initiatives for payment-network applications, including fraud, risk, merchant intelligence, and monitoring. Partners with data scientists, engineers, and product managers to build scalable models and AI tools. Responsibilities span model design, training, evaluation, validation, and implementation using Python, AWS, H2O, Spark, and other technologies. The role also requires stakeholder communication, innovation, and team talent development.

Owns core processing capabilities across the B2B credit lifecycle, leading product strategy, execution, modernization, scalability, resiliency, and security. Partners with technology, operations, credit, marketing, business development, and enterprise platform teams to improve customer experiences, deliver new capabilities, and strengthen product culture.

Provide high-level administrative support to multiple legal executives: manage complex calendars, coordinate travel and expenses, plan meetings and team events, handle communications and information flow, and act as a team ambassador to ensure efficient, organized operations.

Leads technical vision and hands-on engineering for high-volume, low-latency payment systems. Responsibilities include architecting scalable distributed platforms, modernizing monoliths into microservices and event-driven systems, defining API and design standards, ensuring performance and operability, mentoring engineers, leading cross-domain initiatives, and partnering with product and architecture leaders on long-term platform strategy.