Lead Machine Learning Scientist (Fintech)

Location: Remote; team members can live and work anywhere in the United States except Hawaii.

Salary: $174K–$224K base salary annually, plus equity.

Company

hirify.global is a U.S. financial technology company building digital products that provide affordable access to liquidity and credit for financially vulnerable consumers.

What you will do

• Build, train, validate, optimize, and deploy machine learning models for synthetic identities, first-party fraud, account takeover, and emerging fraud patterns.
• Explore large datasets, engineer predictive features, evaluate modeling approaches, and convert findings into production-ready fraud solutions.
• Own the full ML lifecycle from research and prototyping through testing, deployment, monitoring, and continuous improvement.
• Use generative AI and AI-assisted tools to improve research, coding, feature development, experimentation, validation, and modeling workflows.
• Analyze model performance, fraud trends, approval rates, and portfolio outcomes to improve detection accuracy, reduce losses, and support responsible growth.
• Partner with Engineering, Product, and Risk Operations to integrate models into production systems and share technical expertise.

Requirements

• 7+ years of hands-on machine learning experience, including personally developing, deploying, and optimizing predictive models in production.
• Deep fraud modeling expertise involving identity fraud, synthetic identities, first-party fraud, and account takeover, ideally in fintech, consumer lending, or financial services.
• Advanced proficiency in Python and SQL, including feature engineering, model development, experimentation, performance evaluation, and production ML systems.
• 4+ years of experience with ML frameworks and cloud technologies, including tools such as TensorFlow, PyTorch, Spark, and cloud-based ML infrastructure.
• Experience using generative AI and AI-assisted tools for research, coding, analysis, experimentation, testing, and model development, with sound judgment in validating outputs.
• Strong analytical and business judgment when evaluating trade-offs across fraud prevention, approval rates, profitability, compliance, and member experience.
• Ability to independently solve complex ML problems, make sound technical decisions, and deliver measurable results.
• Strong communication and collaboration skills, including explaining technical findings, partnering across functions, and mentoring fellow scientists through hands-on expertise.
• Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field, or equivalent practical experience.

Nice to have

• Experience with graph databases, graph-based fraud detection, or network analytics.

Culture & Benefits

• Virtual-first work culture with flexible hours and a home office stipend.
• Premium medical, dental, and vision insurance.
• Paid parental and caregiver leave, flexible PTO, and company holidays including Juneteenth and Winter Break.
• 401(k) savings plan with matching contributions, financial advisor access, and financial wellness support.
• Flexible learning and growth opportunities, with all-company in-person events once or twice a year and virtual events.
• Culture centered on member focus, transparency, persistence, collaboration, technical excellence, meaningful ownership, and sustainable performance.