Remote Senior ML Lead - Credit Risk & Production Models

Kafene; New York (NY); On-site; USD 145,000 - 170,000; Full time

Benefits offered by this job

Healthcare coverage 80%

401k retirement plan

Paid time off

Job summary

Kafene is hiring a Manager of Data Scientist, a senior individual contributor who will own the full lifecycle of ML models powering credit risk decisions. You will design, build, deploy, and monitor models that determine approvals, credit amounts, defaults, and losses, partnering with risk, engineering, finance, and sales.

You will lead feature engineering, model development, data preparation, vendor evaluation, and governance, ensuring production readiness and regulatory compliance while

Qualifications

• Master's degree or PhD in Statistics, Mathematics, Data Science, Econometrics, or related field.
• 7+ years as Data Scientist or ML Engineer focusing on predictive modeling (credit risk, fraud, finance).
• Experience deploying models affecting real credit decisions.
• Advanced Python for statistical modeling and ML.
• Strong SQL for data extraction and feature construction.
• Expertise in ML algorithms for structured/tabular data (GBMs, ensembles, regression, trees).

Responsibilities

• Own end-to-end ML model lifecycle from design to production.
• Develop and improve credit risk models including approval and loss forecasting.
• Prepare, clean, and transform real-world financial data for modeling.
• Evaluate third-party data vendors and scoring products.
• Collaborate with risk, engineering, finance, and sales to translate questions into modeling solutions.
• Partner with engineering for production validation and deployment.

Skills

Advanced Python

Strong SQL

ML for tabular data

Model risk governance

Communication skills

Education

Master's or PhD

Tools

AutoML

Validation frameworks

Job description

Kafene is hiring a Manager of Data Scientist, a senior individual contributor who will own the full lifecycle of ML models powering credit risk decisions. You will design, build, deploy, and monitor models that determine approvals, credit amounts, defaults, and losses, partnering with risk, engineering, finance, and sales.

You will lead feature engineering, model development, data preparation, vendor evaluation, and governance, ensuring production readiness and regulatory compliance while