Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Preferred qualifications:
8 years of experience in full-stack development for end-to-end machine learning solutions.
Experience building Agentic tools and systems (production-ready, not POCs).
Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows.
Experience in classical ML modeling (e.g., time-series forecasting, tree-based models) alongside modern Large Language Model (LLM)/Generative AI tooling.
Demonstrated expertise in developing and deploying AI or ML models and utilizing modern observability/monitoring tools to track performance, latency, and model drift.
Excellent communication and storytelling skills, with an ability to translate complex technical architectures and probabilistic model behaviors to executive finance leadership.