Senior Manager of Machine Learning
New
K
KafeneFintech
Remote talent across the globeFull-TimeManager
Salary95,000 - 140,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLMachine LearningFinancial analysis
Requirements
- Master's or PhD in a quantitative discipline (Data Science, Statistics, Mathematics, Computer Science, Engineering, or related field) preferred
- 5+ years of hands-on experience as a Data Scientist or Machine Learning Engineer
- Strong track record of building and deploying models in credit risk, fraud detection, or financial analytics
- Advanced Python proficiency with demonstrated experience building production-grade ML models
- Strong SQL skills for data querying and manipulation
- Deep knowledge of ML algorithms including gradient boosting, ensemble methods, regression models, decision trees, and AutoML frameworks
- Prior experience in lending, fintech, or financial services is highly preferred
- Familiarity with model risk governance frameworks and experience working with validation teams is a plus
- Able to translate complex technical concepts clearly for both technical peers and executive stakeholders
Responsibilities
- Analyze internal and external datasets to surface trends and build high-signal features that improve the accuracy and predictive power of our credit models.
- Design and develop strategic ML models end-to-end, including approval amount sensitivity models.
- Manipulate, clean, and transform structured and unstructured data to ensure quality and readiness for modeling.
- Partner with external data vendors to assess third-party data products and scoring solutions.
- Stay at the forefront of machine learning and feature engineering advances.
- Collaborate with technology and engineering teams to implement and validate models with precision.
- Proactively track model performance in production and lead calibration and redevelopment efforts.
- Ensure all models meet regulatory standards and data vendor usage policies.
- Work closely with risk management, engineering, finance, and sales to translate business challenges into scalable, data-driven solutions.
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