Lead AI/ML project delivery, from requirements gathering and prototyping to production deployment and maintenance.
Architect and develop advanced machine learning, deep learning, and analytics models using Python and industry-standard libraries.
Design, implement, and maintain AI governance frameworks—including model documentation, explainability, monitoring, compliance, and auditability.
Collaborate with legal, compliance, and business teams to assess and mitigate AI risk, and ensure models comply with data privacy regulations (e.g., GDPR, CCPA).
Mentor, coach, and develop data science and engineering staff through best practices in coding, testing, peer review, and ethical AI.
Oversee data management, data quality, and secure data access to enable ethical and compliant use of data in AI projects.
Monitor deployed AI models for drift, bias, performance, and regulatory alignment, drive model retraining and revalidation cycles.
Communicate technical results, risks, and governance strategies to technical and non-technical stakeholders.
Stay abreast of the latest AI, ML, and governance innovations, integrating emerging tools and techniques into the organization.
Lead selection and integration of AI tools, platforms, and frameworks to accelerate development and ensure governance coverage.