Senior Machine Learning Scientist (Fintech)

Location: Remote within the United States; Hawaii excluded

Salary: $150,000–$187,000 per year, plus equity

Company

hirify.global is a virtual-first fintech company building digital financial products for Americans underserved by traditional financial institutions.

What you will do

• Develop and optimize underwriting, settlement, and collection strategies across ExtraCash, FlexCard, and Rent.
• Build machine learning and AI-enabled credit strategies using cash-flow, income, behavioral, bureau, and alternative data.
• Design experimentation frameworks with success metrics, scenario analyses, guardrails, and launch recommendations.
• Partner with Product, Engineering, ML Platform, Finance, Legal, and Compliance on scalable decisioning solutions.
• Monitor portfolio and business performance and turn risks and opportunities into actionable recommendations.
• Build reusable workflows for modeling, testing, validation, documentation, and monitoring.

Requirements

• 5+ years of experience in consumer credit risk, underwriting, machine learning, or predictive analytics, ideally in fintech or consumer lending.
• Hands-on experience with statistical modeling, machine learning, experimentation, and production decision systems.
• Proficiency in Python and SQL.
• Experience developing credit strategies across the full product lifecycle and working with alternative data.
• Experience using AI-assisted tools across research, coding, analysis, model development, testing, or documentation.
• Bachelor’s or master’s degree in computer science, mathematics, statistics, economics, engineering, or another quantitative discipline.

Nice to have

• PhD in a quantitative discipline.

Culture & Benefits

• Virtual-first culture with flexible hours and a home office stipend.
• Premium medical, dental, and vision insurance.
• Paid parental and caregiver leave.
• 401(k) savings plan with matching contributions.
• Financial wellness support, flexible PTO, and company holidays.
• All-company in-person events once or twice a year, plus virtual events.