Top Tech Jobs & Startup Jobs in Chicago, IL

The Product Security Engineer partners with Engineering and Product teams to embed security throughout the development lifecycle. Responsibilities include threat modeling, architecture and security reviews, vulnerability validation, remediation planning, security-tool ownership, automation, secure coding guidance, incident response, and assessing risks in cloud and AI-enabled products. The role requires strong application security, identity, authentication, authorization, coding, communication, and cross-functional collaboration skills.

Manages the full accounts receivable cycle, including invoicing, collections, cash application, reconciliations, discrepancy resolution, and customer communications. Reviews APAC payroll transactions in NetSuite, supports month-end close, prepares journal entries and account reconciliations, analyzes financial variances, and assists with annual audits and special accounting projects.

Own product positioning and go-to-market strategy for YipitData’s AI and big data products serving public investors. Define customer segments and messaging, lead product launches, conduct competitive intelligence, support pricing and packaging, and create sales enablement materials. Partner with Product, Revenue, and Insights teams to shape the roadmap and drive adoption. Establish GTM success metrics, monitor performance, and improve strategies across data feeds, software, and AI-powered investor solutions.

The Director of Strategic Data Partnerships will identify and execute exclusive data partnerships, engaging with executives to build alignment and negotiate complex agreements. This role focuses on strategic judgment and ongoing relationship management to drive product development and growth.

Lead AI product strategy for investor workflows, building AI-native products (agents, copilots, MCPs, APIs) that turn proprietary data into reliable, production-grade investor tools. Partner with customers, engineering, design, and research to run experiments, define quality/trust frameworks, and ship 0→1 products that automate and augment investment decision-making.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.

Own and QA high-impact retail data products: design and run QA, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, improve automation and product reliability, and communicate methodology and limitations to clients.

Build and own end-to-end, production-grade full‑stack features across backend, frontend, data pipelines, and infrastructure. Collaborate with stakeholders to translate business problems into shipped software, drive cross-team initiatives, and improve tooling and code quality. Use AI coding tools daily to accelerate development and maintain reliability for customer-facing products.

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.

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.