Top Tech Jobs & Startup Jobs in Chicago, IL

Drive high-volume outbound re-engagement of paid-in-full merchants to generate new funding opportunities. Use CRM (Salesforce) and auto-dialer tools, analyze performance metrics, mentor junior reps, collaborate with cross-functional teams, pilot beta technologies, and meet strict activity, conversion, and quota targets.

As a Collections Specialist, you will manage SMB customer accounts, negotiate payment plans, achieve recovery targets, and document accounts in Salesforce CRM.

Manage a portfolio of small and medium business customers to grow relationships and identify additional capital solutions. Analyze business and financial histories, own the sales process from approval to close, use data to prioritize opportunities, and meet monthly quota in a fast-paced environment.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Design, build, and operate a low-latency online feature store and supporting batch/streaming pipelines. Optimize Postgres schemas and real-time serving for ML models, improve scalability, reliability, and observability, mentor junior engineers, and partner with data science, analytics, product, and application teams to deliver production-grade MLOps solutions.

This role is responsible for prospecting and converting financing applications, engaging with small business owners, and driving measurable sales results through lead conversion.

The Senior Analyst, Portfolio Strategy will analyze pricing and credit strategies, manage portfolio risk, and support decision-making with data insights.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Implement, configure, and test decision engine process flows and rule changes. Execute QA, A/B tests, and historical backtesting. Validate data integrity between vendors and core apps. Gather requirements, document processes, and collaborate with Pricing, Risk, and Engineering to ensure accurate, efficient decisioning.