Establish and enforce best practices for ML modeling while driving adoption of modern tools, frameworks, and infrastructure.
Foster a culture of innovation, experimentation, and collaboration and mentor a team of data scientists.
Partner with product, engineering, data, and compliance teams to integrate ML into products and communicate complex concepts to diverse audiences.
Collaborate with Data Science leaders to establish an operating model for ML R&D that optimizes delivery of business value.
Experience Requirements
Bachelor’s or master’s degree in computer science, statistics, mathematics, engineering, or related field. PhD preferred.
7+ years in ML research or engineering and 5+ years building large-scale, real-time ML systems in production with hands-on experience.
Expertise in machine learning, statistical modeling, and data analysis with strong experience across the ML lifecycle and experimentation.
Proficiency in Python (Pandas, NumPy, scikit-learn) and strong SQL. Experience with NoSQL or graph databases is a plus.
Demonstrated ability to lead solution design and execution, translating complex business requirements into actionable technology solutions.
Exceptional verbal and written communication skills with the ability to influence and collaborate across technical and business audiences, including executives.
Bonus: Experience in payments, fintech, or financial services. Knowledge of payment systems, fraud and risk, or real-time payments. Experience with AWS, GCP, Snowflake, Databricks, or Vertex AI. Agile development experience. Background in large companies, mature ML teams, or regulated industries.
Education Requirements
Bachelor’s or master’s degree in computer science, statistics, mathematics, engineering, or related field. PhD preferred.
