Applied Machine Learning Manager - Application Fraud
S
SentiLinkFintech / Identity
United StatesFull-TimeManager
Salary$200,000-$250,000/year + equity + benefits
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Job Details
- Experience
- 6+ years of industry experience applying machine learning or statistics to real-world problems, including 3+ years directly managing machine learning or data science teams.
- Required Skills
- AWSPostgreSQLPythonElasticSearchMachine LearningPandasscikit-learn
Requirements
- 6+ years of industry experience applying machine learning or statistics to real-world problems.
- 3+ years directly managing machine learning or data science teams.
- Experience leading teams in fraud, identity, fintech, banking, financial services, or payments.
- Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, Physics, or related quantitative discipline.
- Demonstrated success developing and deploying production machine learning models.
- Experience writing production-quality Python code and tests.
- Strong practical ML and applied statistics knowledge.
- Track record of measurable business impact and end-to-end project execution.
- Experience with modern LLMs and AI-assisted development workflows.
- Sound judgment in data governance and security.
Responsibilities
- Directly manage a team of applied ML scientists and set engineering and modeling practices.
- Own execution for your area including priorities, delivery, and results.
- Coach and mentor team members through model development, experimentation, and technical decision making.
- Remain hands-on with code review and production systems.
- Partner with senior leadership, Product, Engineering, and Risk to prioritize and deliver ML solutions.
- Communicate progress, tradeoffs, and results clearly to stakeholders.
- Develop and improve fraud detection and identity models across the full lifecycle (data acquisition, feature engineering, training, deployment, monitoring).
- Research emerging fraud patterns and build new ML capabilities for financial risk.
- Integrate AI throughout the team's work and contribute to product exploration.
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