10-12 years in data science/AI/advanced analytics, with over 5 years leading AI programs/products at scale; prior experience in risk, compliance, audit, or financial services preferred. Proven track record delivering production-grade AI/ML solutions with tangible business impact in regulated environments. Hands-on understanding of ML (supervised/unsupervised), NLP/LLMs/GenAI, graph analytics, anomaly detection, time-series, and decision intelligence. Strong command of MLOps (CI/CD for ML, model monitoring, drift management), data engineering, and model evaluation/validation; proficiency with Python and modern ML stacks; familiarity with cloud services, containerization, and orchestration; working knowledge of enterprise data platforms. Practical experience with responsible AI, model governance, documentation, validation, and audit readiness; privacy-by-design mindset. Experience with prompt engineering and LLM evaluation frameworks (e.g., guardrails, red-teaming, offline/online evaluation), and with experiment design (A/B testing, hypothesis-driven development). Excellent stakeholder management and influence skills; able to translate technical concepts into business outcomes for senior leaders and global teams. Candidates should be prepared to present case studies of prior AI/ML initiatives, governance alignment, and measurable business outcomes. Bachelor's degree required; advanced degree in a relevant discipline preferred.
