Applied Machine Learning Manager - Application Fraud

Ovii's Interpretation of the Role

Lead a growing team of applied ML scientists to build fraud detection and identity verification models for US financial services. Own the end‑to‑end ML lifecycle, partner with product and engineering leaders, and drive AI safety and data governance. Hands‑on manager who mentors, codes, and ships production‑grade models.

Role Snapshot

• Manage applied ML team
• Own fraud detection model lifecycle
• Partner with product & engineering leadership
• Mentor and code‑review ML scientists
• Advance AI/LLM tooling and safety

Must-Have Requirements

• Python
• XGBoost
• scikit-learn
• pandas
• PostgreSQL
• AWS
• Elasticsearch/OpenSearch
• Neo4j
• MLflow
• Flyte
• LLM tooling
• Applied statistics
• machine learning
• statistics
• team management
• Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, Physics, or quantitative discipline
• must be legally authorized to work in the United States
• must live in the United States

Nice-to-Have Signals

• high‑growth startup experience
• high‑growth startup
• fintech/fraud domain

Work Setup

• Location: United States
• Work mode: REMOTE
• Remote scope: COUNTRY_RESTRICTED
• Remote countries: United States
• Employment type: Full-Time

Eligibility Gates

• Work authorization: must be legally authorized to work in United States
• Visa sponsorship: no

Not Specified in JD

• Visa sponsorship

What You'll Likely Work On

• Directly manage and grow a team of applied ML scientists, setting engineering and modeling standards
• Define priorities, drive delivery, and own results for your ML domain
• Coach, mentor, and stay hands‑on with code reviews and production systems
• Partner with senior leadership, product, engineering, and risk teams to prioritize impactful ML solutions
• Communicate progress, trade‑offs, and outcomes while shaping product strategy
• Develop fraud detection and identity models across the full lifecycle from data acquisition to monitoring
• Research emerging fraud patterns and build new ML capabilities that inform product and business decisions
• Leverage modern LLMs and AI tools to expand what the team can achieve

Good Fit If You Have

• Experience leading ML or data‑science teams in fintech, banking, payments, or related risk domains
• Background in high‑growth startup environments
• Comfortable experimenting with LLMs and AI‑assisted development
• Strong communicator who can influence product strategy