Lead Machine Learning Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop, train, validate, and enhance sophisticated fraud detection models.

• Identify synthetic identities, first-party fraud, account takeovers, and new fraud patterns.

• Analyze extensive, diverse datasets and create predictive features.

• Assess modeling techniques and convert insights into production-ready fraud solutions.

• Oversee the machine learning lifecycle from research and prototyping to testing, deployment, monitoring, and ongoing improvement.

• Utilize modern AI tools and methodologies to enhance research, coding, feature development, experimentation, validation, and modeling workflows.

• Analyze model performance, fraud trends, approval rates, and portfolio results.

• Enhance detection accuracy, minimize losses, and promote responsible growth.

• Collaborate with Engineering, Product, and Risk Operations to implement models into production systems.

• Address implementation challenges and disseminate technical knowledge.

• Report directly to the Director of Risk Science.

⛳️ Requirements

• Over 7 years of practical experience in machine learning.

• Proven history of personally developing, deploying, and optimizing predictive models in live production settings.

• In-depth expertise in fraud modeling, encompassing identity fraud, synthetic identities, first-party fraud, and account takeovers.

• Ideally experienced in fintech, consumer lending, or financial services sectors.

• Advanced skills in Python and SQL.

• Strong background in feature engineering, model development, experimentation, performance assessment, and production ML systems.

• 4+ years of experience with ML frameworks and cloud technologies, including tools like TensorFlow, PyTorch, Spark, and cloud-based ML infrastructure.

• Experience utilizing generative AI and AI-assisted tools in research, coding, analysis, experimentation, testing, and model development.

• Robust analytical and business judgment regarding fraud prevention, approval rates, profitability, compliance, and member experience.

• Capability to independently address complex ML challenges, make informed technical decisions, and achieve measurable outcomes.

• Excellent communication and collaboration abilities.

• Proficient in conveying technical findings, collaborating across functions, and mentoring fellow scientists.

• Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative discipline, or equivalent practical experience.

• Familiarity with graph databases, graph-based fraud detection, or network analytics is a plus.

• Must be permanently authorized to work in the United States without visa sponsorship.

🏝️ Benefits

• Opportunity to confront challenging problems, learn and grow alongside top talent, and assist millions in achieving their personal financial objectives.

• Flexible hours and a virtual-first work culture with a home office stipend.

• Premium Medical, Dental, and Vision Insurance plans.

• Generous paid parental and caregiver leave.

• 401(k) savings plan with matching contributions.

• Access to financial advisors and financial wellness support.

• Flexible PTO and generous company holidays, including Juneteenth and a Winter Break.

• Company-wide in-person events once or twice a year and virtual events throughout the year to connect with team members and leadership.

• Equity offered.