Top Tech Jobs & Startup Jobs in Chicago, IL

The Client Strategy Manager will manage client relationships, develop commercial strategies, and ensure client success through proactive engagement and support. This role includes account management, upselling, and enhancing client engagement with the firm's analytics services.

As a Research Analyst, you'll drive fundamental research for subscription-based data products, analyze large datasets, and collaborate with teams to offer insights and develop new products.

The Business Development Manager will manage client relationships, identify upsell opportunities, run the sales process, and negotiate agreements while collaborating with internal teams to assist clients.

The Account Development Manager will manage client relationships, drive client engagement, execute growth strategies, and develop commercial strategies for renewals and upsells.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Lead AI product strategy for investor workflows, designing AI-native products (agents, copilots, MCPs, APIs). Partner with investors, engineers, researchers, and designers to translate LLMs, retrieval, and agent architectures into reliable, production-grade features. Drive rapid experimentation, define evaluation and trust frameworks, and shape platform evolution for investor-grade AI products.

Design end-to-end UX for an AI-powered B2B data product. Translate complex AI and data concepts into intuitive, trustworthy interfaces; conduct user research; define workflows; collaborate with Product, Engineering, and Data Science; contribute to design systems and maintain design quality through launches.

Design, validate, and deploy scalable statistical and distributional models for enterprise consumer analytics. Implement rigorous methodologies, convert ad-hoc analyses into version-controlled analytical libraries, and partner with Data Engineering to optimize performance and scale compute workloads (including cloud/Databricks). Deliver reproducible analytics powering dashboards and LLM-driven applications, with a focus on panel and transaction-level consumer data.

Lead the Central Data Platform roadmap: define and prioritize capabilities, translate business needs into technical requirements, coordinate cross-functional execution, measure adoption and data quality, and drive continuous platform improvements to increase reuse and business impact.

Lead operational management of the Product Classification organization: hire, train, and scale classification and manual QA teams; set metrics, SLAs, and operating cadence; partner with Engineering and Product to improve LLM-driven classification; build processes, rules, and analytic checks to ensure high accuracy at scale.