Kafene is hiring a
Director of Machine Learning

Summary

Join our growing team as we seek a highly skilled Director or Manager of Machine Learning Engineering to develop, deploy, and monitor machine learning models that drive credit risk assessments. As a key contributor, you will collaborate with cross-functional teams to understand business challenges and translate them into data-driven solutions.

Requirements

• Advanced Degree: A Master’s or PhD in a highly quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related discipline is preferred
• Experience: 3+ years of hands-on experience as a Data Scientist or Machine Learning Engineer, with a strong focus on developing and deploying machine learning models in areas such as credit risk, fraud detection, or marketing analytics
• Technical Requirement: Advanced proficiency in Python, with a proven track record of developing complex machine learning models
• Technical Requirement: Strong SQL skills are essential for efficient data manipulation and querying
• Technical Requirement: In-depth knowledge of machine learning algorithms and techniques, including decision trees, regression models, gradient boosting machines, ensemble methods, AutoML tools, etc
• Model Governance: Experience with model risk governance frameworks and collaboration with model validation teams to ensure compliance with industry standards and regulatory requirements is a plus
• Industry Knowledge: Previous experience in the lending or financial services industry is highly preferred, particularly in the context of credit, fraud, marketing, or other financial applications

Responsibilities

• Feature Engineering: Lead in-depth analysis of internal and external datasets to identify trends and generate actionable insights
• Data Manipulation: Expertly manipulate, clean, and transform both structured and unstructured data to prepare it for robust modeling
• Model Development: Take a central role in designing and developing strategic models
• Vendor Evaluation: Collaborate with various external data vendors to evaluate third-party data and scoring products
• Research and Implementation of Advanced Techniques: Stay ahead of the curve by researching and incorporating the latest machine learning algorithms and feature engineering techniques into model development
• Model Compliance: Stay informed on emerging regulatory requirements and industry trends to ensure all models adhere to best practices in compliance
• Model Implementation and Validation: Work closely with technology and engineering teams to accurately implement and validate models
• Model Monitoring and Maintenance: Proactively monitor model performance, identifying any issues or deterioration
• Model Documentation and Governance: Ensure all credit risk models are thoroughly documented, including development processes, assumptions, methodologies, and validation procedures
• Cross-Functional Collaboration: Collaborate closely with teams across risk management, technology, engineering, finance, and sales to gather data, understand business requirements, and align credit risk modeling efforts with broader business objectives

Benefits

• Base Salary: Earn a competitive base salary ranging from $130,000 to $190,000
• Healthcare: We prioritize your well-being by covering 80% of medical, dental, and vision insurance costs, including coverage for your spouse, children, and other dependents
• Retirement Benefits: Begin planning for your future from day one with our 401k plan
• Paid Time Off: We understand the importance of work-life balance. That's why we offer flexible paid time off days starting from day one of your employment