Position Details
About this role
Lead a team of data science associates to build machine learning models used for critical credit decisioning. Partner with cross-functional teams to deliver improved personalization for acquisitions and retention growth.
Key Responsibilities
- Lead a team of 4-5 associates to build next generation ML models for credit decisioning
- Partner with data science, software engineering, and product teams to deliver customer-facing outcomes
- Develop ML models from design through training, evaluation, validation, and implementation
- Apply statistical modeling and interpret model diagnostics (confusion matrix, ROC curve)
- Translate modeling complexity into tangible business goals
Technical Overview
Hands-on data science leadership focused on machine learning model development across the full lifecycle, including evaluation and validation. Uses a broad stack including Python, Conda, AWS, H2O, and Spark, with strong statistical modeling and model diagnostic capabilities (confusion matrix, ROC curve).
Ideal Candidate
The ideal candidate is a senior data science leader who has built and operationalized machine learning models end-to-end (design, training, evaluation, validation, and implementation). They are hands-on with Python and modern big data tooling like AWS, Spark, and H2O, and they can demonstrate strong statistical modeling through backtesting and model diagnostics such as confusion matrices and ROC curves.
Must-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Must demonstrate hands-on experience developing and validating machine learning models (design, training, evaluation, validation, implementation), Must have model evaluation experience including confusion matrix or ROC curve, Must have leadership experience leading a team of associates
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