Senior/Staff Data Scientist (Fintech)

TL;DR

Senior/Staff Data Scientist (Fintech): Building and improving predictive models for consumer decisioning and business optimization across a financial services portfolio with an accent on cash-flow based credit decisioning and fraud scoring. Focus on owning the full model development lifecycle, designing reusable modeling pipelines, and implementing MLOps practices.

Location: Hybrid (Chicago, IL: 4 days in-office, 1 day remote)

Company

hirify.global powers Klover, one of the fastest-growing fintech platforms in the U.S., providing real-time financial tools and rewards to over one million active users monthly.

What you will do

• Develop and deploy ML and statistical models for credit decisioning, consumer behavior, fraud, and churn prediction.
• Own the full model development lifecycle, including data exploration, feature engineering, validation, and monitoring.
• Build reusable modeling pipelines and production-quality code to support scalable data science work.
• Collaborate with product managers, engineers, and business stakeholders to deliver high-precision ML models.
• Identify and implement new data science and optimization opportunities to improve business outcomes.

Requirements

• 5+ years of experience as a Data Scientist, ML Scientist, or similar quantitative role.
• Master's or Ph.D. in a STEM field (Computer Science, Statistics, Economics, Mathematics, etc.).
• Strong proficiency in Python and SQL for working with large, complex datasets.
• Expertise in developing, validating, and monitoring production-grade ML models.
• Experience with GCP and MLOps practices.
• Must be based in Chicago, IL and follow the hybrid schedule (4 days in-office)

Nice to have

• Experience with LLMs or autonomous agents for code generation and model refinement.
• Background in risk modeling, credit decisioning, or fraud modeling.

Culture & Benefits

• Work on high-impact systems processing over $1.5 billion annually.
• Collaborative environment working across backend, frontend, and product teams.
• Opportunity to define the next generation of inclusive, data-powered financial products.
• Modern technology stack focusing on reliability, privacy, and performance at scale.