Director of Data Science- Credit Risk Scoring

Job description

We are looking for an experienced and experienced Director of Data Science to lead our data science projects with a focus on credit risk scoring. We are looking for expertise in building, implementing, and optimizing credit risk models, including machine learning (ML) models, and the ability to manage a team of data scientists.

You are a hands-on coder with experience using data-driven insights to lead decision-making. You have a background in modeling and experience of Python, with demonstrated experience delivering solutions to complex credit risk challenges. As a Director, Data Science you will be reporting to the VP, Analytics Products Build.

Responsibilities:

• Build, and mentor a team of data scientists specializing in credit risk modeling.
• Build the data science strategy for credit risk modeling and analytics with our goals.
• Collaborate with teams, including product, engineering, and compliance, to integrate models into our workflows.
• Hands-On Development:
• Design scalable, accurate, and explainable credit risk models and models solving problems across the entire credit life-cycle using machine learning and traditional statistical techniques.
• Write high-quality, production-grade Python code to prototype and implement models.
• Ensure comply with regulatory requirements and company policies.
• Analyze large datasets to identify trends and drivers of credit risk, ensuring applicable insights for partners.
• Develop approaches to feature engineering and data enrichment to improve model performance.
• Maintain existing models, ensuring they remain up-to-date with changing data and our needs.
• Communicate technical concepts and model outcomes to non-technical partners.
• Provide strategic insights to executive leadership based on data science outcomes.

Qualifications:

• Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• 8+ years of experience in data science, with a focus on credit risk modeling.
• Experience leading teams.
• Hands-on experience developing and deploying machine learning models, especially in credit risk contexts.
• Fundamental knowledge in general processes around targeting, Fraud detection, acquisitions, Account management, collections
• Technical Expertise:
• Advanced proficiency in Python and main libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
• Knowledge of statistical modeling, feature engineering, and machine learning algorithms.
• Experience working with big data technologies and distributed systems (e.g., Spark, Hadoop).
• Knowledge of credit risk scoring methodologies, regulatory frameworks, and model governance.
• Experience scrapping data and parsing unstructured data

Qualifications:

• Capabilities with the ability to inspire and mentor team members.
• Translate complex technical details into applicable insights for diverse partners.
• Thinker with a creative approach to the ability to develop unique solutions
• Experience with Visualization tools such as Tableau

Benefits

• Health, Dental, Vision Insurance
• 401k match up to 4% of 100% of your salary
• 20% app bonus target
• Remote work environment #li-remote