Applied Machine Learning Manager - Application Fraud
Leads and manages an applied machine learning team developing production fraud detection and identity verification models. The role combines people leadership with hands-on technical work and requires substantial ML experience, production deployment expertise, and experience in risk-focused domains.
About the job
Responsibilities
- Directly manage and grow a team of applied ML scientists, establishing engineering and modeling practices.
- Own priorities, execution, delivery, and results for the team’s domain.
- Coach and mentor team members through model development, experimentation, and technical decisions.
- Remain hands-on through code review and production systems.
- Partner with senior leadership, Product, Engineering, and Risk to prioritize work and deliver impactful ML solutions.
- Communicate progress, tradeoffs, and results, and represent the domain in product strategy discussions.
- Develop and improve fraud detection and identity models across data acquisition, feature engineering, labeling, training, experimentation, deployment, monitoring, and iteration.
- Research emerging fraud patterns and build ML capabilities for identity verification and financial risk.
- Design analyses that inform product and business decisions.
- Use AI across team workflows and help evaluate AI applications within products.
Requirements
- 6+ years of industry experience applying machine learning or statistics to real-world problems.
- 3+ years of direct management experience leading machine learning or data science teams.
- Experience leading teams in fraud, identity, fintech, banking, financial services, payments, or related risk domains.
- Bachelor’s, master’s, or PhD in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline.
- Demonstrated success developing and deploying production machine learning models.
- Production-quality Python code and testing experience.
- Strong practical machine learning and applied statistics knowledge.
- Experience delivering measurable business impact across planning, solution development, and execution.
- Familiarity with modern LLMs and AI-assisted development workflows.
- Sound judgment with sensitive data, information security, and data governance constraints.
- Strong communication, mentoring, decision-making, and collaboration skills.
- Must be legally authorized to work in the United States and live in the United States.
Technologies
- Python 3
- PostgreSQL
- AWS
- XGBoost
- scikit-learn
- pandas
- Elasticsearch
- OpenSearch
- Neo4j
- MLflow
- Flyte
- Large language models
Compensation & Benefits
- $200,000-$250,000/year plus equity and benefits.
- Employer-paid group health insurance for employees and dependents.
- 401(k) plan with employer match.
- Flexible paid time off.
- Regular company-wide in-person events.
- Home office stipend.
Skills
Python, Postgres, AWS, Xgboost, scikit-learn, pandas, Elasticsearch, Opensearch, Neo4J, MLflow, Flyte, LLMs, Machine Learning, Applied Statistics, Fraud Detection
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