Principal Data Scientist, Windfall

• If you are a driven, detail-oriented data scientist with experience in model risk management (OCC standards), who thrives on building and deploying complex machine learning models at scale, we’d love to hear from you
• At least 8 years experience working directly with machine learning models
• Advanced proficiency in machine learning techniques and statistical modeling
• Expert in Python, with a strong track record of building, deploying, and maintaining machine learning models at scale
• Experience handling large, diverse datasets from multiple sources
• Impeccable attention to detail in both model development and result reporting
• Strong ability to communicate technical concepts and complex model outputs clearly and effectively to non-technical stakeholders

Desirable

• We are looking for a seasoned Principal Data Scientist to play a pivotal role in developing and scaling our foundational predictive models, such as household net worth and investable assets
• This is a highly impactful role where you will influence the core of our data product offerings and collaborate with cross-functional teams to maintain the highest standards of model performance
• Model Training & Deployment: Lead the training and production deployment of Windfall’s foundational models, focusing on predicting key financial metrics like household net worth and investable assets
• Model Performance Analysis: Analyze and monitor the performance of machine learning models, ensuring they meet business goals and adhere to model risk management standards
• Documentation & Communication: Document modeling processes with a high level of rigor and transparency. Effectively communicate key performance metrics and model insights to business stakeholders, ensuring clarity and alignment
• Model Risk Management: Ensure compliance with OCC Model Risk Management standards, implementing processes for model validation, testing, and monitoring
• Data Handling: Work with large, disparate sources of data to build robust and stable models that are resilient in real-world applications
• Cross-Functional Collaboration: Partner closely with engineers, analysts, and business stakeholders to design and implement models that deliver actionable insights and drive business outcomes