Applied AI/ML Modeling, Vice President

What you'll do

• Develop and launch AI/ML models for lead scoring, propensity modeling, and next-best-action to improve banker sales effectiveness.
• Lead modeling engagements end-to-end from scoping use cases and defining success metrics to building project plans.
• Formulate testable hypotheses by analyzing large, complex datasets to solve ambiguous business problems.
• Translate complex model outputs into clear, actionable recommendations and narratives for non-technical business partners.
• Partner with governance and risk teams to ensure models meet regulatory standards and undergo thorough reviews.
• Monitor model performance and drift while documenting model intent and limitations.
• Deploy models into production environments using MLOps best practices for monitoring and retraining.

What we're looking for

• Master's or Ph.D. in a quantitative discipline such as Computer Science, Statistics, Machine Learning, Econometrics, Operations Research, Applied Mathematics, or a related field.
• 5+ years of hands-on, relevant industry experience developing and deploying AI/ML models in production.
• Proficiency in Python with hands-on experience in ML/deep learning frameworks like TensorFlow or PyTorch and libraries like NumPy, Scikit-Learn, and Pandas.
• Deep expertise in at least one and meaningful exposure to another of recommendation systems, ranking, constrained optimization, causal inference, online learning, or behavioral modeling.
• Demonstrated ability to communicate complex modeling concepts clearly to non-technical stakeholders and drive decisions.
• Ph.D. in a relevant discipline (preferred).
• Experience developing advanced AI/ML models in consumer finance, fintech, retail, marketplaces, or other high-scale customer engagement environments (preferred).
• Experience with specific decisioning/online learning libraries, causal inference tooling, behavioral science concepts, or MLOps platforms like Databricks and Snowflake (preferred).