Lead Data Scientist (Credit Risk)

Location: Chicago, IL, USA, or San Francisco, CA, USA; the in-office policy requires four days per week in the office and Fridays from home for employees near an office.

Base salary: $152,000–$210,000 USD per year, plus potential bonuses, equity, and benefits.

Company

hirify.global is a financial technology company providing consumer banking services and tools designed to help members achieve financial progress.

What you will do

• Own credit strategy for new-to-hirify.global applicants across Instant Loans and future unsecured products such as credit cards and lines of credit.
• Develop channel-specific credit policies covering prescreening, pre-approval, direct mail, open applications, referrals, and affiliates.
• Design acquisition, loan amount, credit line, pricing, repayment, and collections strategies.
• Build and iterate credit models using bureau, alternative, and internal data in partnership with data science and machine learning teams.
• Lead champion/challenger tests and controlled ramps while measuring approvals, losses, direct deposit conversion, and lifetime value.
• Partner with Finance, Strategy, Product, Engineering, Compliance, Legal, Fraud, Model Risk Management, and bank partners to launch and govern credit strategies.

Requirements

• Master’s degree in Statistics, Economics, Engineering, Mathematics, Finance, Computer Science, or another quantitative discipline; PhD is a plus.
• 7+ years of analytical or data science experience in financial services, preferably in FinTech.
• 4+ years of experience building and managing unsecured credit products, including installment loans, lines of credit, or credit cards.
• Hands-on experience with credit bureau data, prescreening, pre-approval, or direct mail credit programs.
• Knowledge of credit furnishing, bankruptcies, delinquency, write-off policies, and consumer lending regulations including FCRA, ECOA/Reg B, fair lending, and adverse action requirements.
• Strong skills in SQL, Python, Microsoft Excel, Looker or a similar BI tool, statistics, machine learning, scorecards, gradient-boosted models, vintage analysis, swap-set analysis, and experiment design.

Nice to have

• Experience with subprime or near-prime lending, affiliate or marketplace lending, credit card line management, or cash-flow and alternative-data underwriting.
• PhD in a quantitative discipline.

Culture & Benefits

• Hybrid in-office policy with four office days and Fridays from home near company offices; a fully remote program is also available for eligible employees.
• Health, financial, and wellbeing benefits, including backup child, elder, and pet care and subsidized commuter benefits.
• Generous vacation, company-wide paid days off, and paid parental leave of up to 22 weeks for birthing parents and 12 weeks for non-birthing parents.
• Annual wellness stipend, family planning reimbursement, and community-support time off.
• Inclusive, entrepreneurial environment focused on financial technology and consumer financial progress.