Director of Data Science- Credit Risk Scoring

Job descriptionWe 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, collectionsTechnical 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 dataQualifications: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 solutionsExperience with Visualization tools such as TableauBenefitsHealth, Dental, Vision Insurance401k match up to 4% of 100% of your salary20% app bonus targetRemote work environment #li-remote