About the Role
I am working with a client looking for a Senior AI/ML Modeling Lead to provide both strategic direction and hands-on oversight across a range of AI/ML initiatives. This individual will guide a team of data scientists and modelers through the end-to-end model lifecycle, promote consistency in modeling practices, and act as a key bridge between technical teams and senior stakeholders.
The ideal candidate brings 9+ years of experience and is comfortable operating across both high-level strategy and detailed technical execution.
Key Responsibilities
- Provide leadership across multiple AI/ML modeling initiatives, ensuring efforts are aligned with broader business priorities
- Oversee models from development through deployment and ongoing monitoring, including performance evaluation, documentation, and maintenance
- Define and uphold standards around modeling approaches, validation techniques, and model transparency
- Partner with cross-functional teams (including risk, compliance, and technology) to address challenges related to model quality and governance
- Support internal review processes to ensure models meet established standards and expectations
- Communicate technical findings and model outcomes to non-technical and executive audiences in a clear, actionable way
- Evaluate emerging tools, techniques, and approaches within AI/ML and recommend adoption where appropriate
- Manage, mentor, and grow a team of modelers, fostering strong technical capability and collaborative culture
- Contribute to longer-term planning and prioritization of modeling and analytics initiatives
- Work closely with partners across data, engineering, and business teams to deliver impactful solutions
Qualifications & Experience
- 9+ years of experience in quantitative modeling, data science, or machine learning, with prior leadership or team oversight experience
- Exposure to a variety of modeling approaches, such as predictive modeling, NLP, or optimization techniques
- Strong programming experience in Python and familiarity with modern ML tools and data environments
- Understanding of model lifecycle considerations, including validation, monitoring, and performance management
- Experience working in environments with structured review, risk, or governance processes
- Demonstrated ability to lead teams and collaborate across functions in fast-paced settings
- Strong communication skills with the ability to present complex concepts clearly
- Track record of evaluating and implementing new tools or methodologies
- Advanced degree in a quantitative discipline preferred