Lead the development and implementation of advanced data science models. Collaborate with stakeholders to understand requirements. Drive best practices in data science. Ensure data quality and integrity in all processes. Mentor and guide junior data scientists. Stay updated with the latest trends in data science. Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience. 5+ years of experience in data science or machine learning, with at least 2 years applying AI/ML to operations, risk, or fraud domains. Strong proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow). Experience with LLMs, prompt engineering, RAG pipelines, or AI agents is a strong plus. Deep understanding of root cause analysis, anomaly detection, or incident forensics. Proven ability to translate business problems into data science solutions. Familiarity with MLOps tools and concepts (e.g., model serving, observability, retraining). Excellent communication skills and a collaborative mindset. Bachelor's or Master's in Computer Science, Statistics, Engineering, or related field. PhD a plus.