AVP - Data Scientist & AI Engineer
Barclays (company site, opens in a new tab)2–3 yrsPuneOn-siteDirect career pageEst. 30–45 LPA
Posted on 7 Sept
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Job description
Structured overview of role & requirements
About This Role
- Lead design, development, and deployment of advanced ML models and AI solutions for risk, compliance, and financial crime domains in a production environment.
- Build and maintain full ML pipelines including data ingestion, feature engineering, model training, validation, deployment, and monitoring adhering to model risk management standards.
- Mentor junior data scientists, contribute to team strategy and AI governance including model explainability, regulatory compliance, and stakeholder communication.
Minimum Requirements
- Master's degree in quantitative discipline (Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering, or related).
- 2–3 years experience in financial services data science or AI/ML, preferably in Risk, Compliance, or regulatory functions with domain knowledge in credit risk, market risk, operational risk, or financial crime.
- Strong proficiency in Python, SQL, big data technologies (Spark, Databricks), and ML frameworks (XGBoost, PyTorch, scikit-learn); experience with cloud platforms (AWS, Azure) and MLOps tools (MLflow, Airflow).
- Role based in Pune; hands-on experience with NLP, generative AI (LLMs, RAG, prompt engineering), and familiarity with AI governance frameworks (SS1/23, BCBS 239) required.
Ideal Candidate Profile
- Technically strong data scientist/ML engineer with operational experience delivering production-grade risk analytics models within regulated financial environments.
- Comfortable balancing hands-on development with leadership responsibilities including mentoring, cross-functional collaboration, and strategic AI roadmap contribution.
- Proficient in navigating AI governance and regulatory compliance for banking risk models, with clear communication skills to articulate complex AI concepts to non-technical stakeholders.