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AVP/VP, Data Scientist, Data Management Office

4-6 Years
  • Posted 3 months ago
  • Be among the first 10 applicants

Job Description

Responsibilities

  • Independently assess AI/ML/data science model purpose, assumptions, features, data inputs, and logical soundness.
  • Evaluate feature engineering, data quality, and detect issues such as leakage or mis-specified inputs.
  • Evaluate model performance using suitable metrics, diagnostic tests, and validation methodologies.
  • Assess stability, robustness, sensitivity analysis, susceptibility to adversarial attacks and model or concept drift.
  • Apply model explainability methods such as SHAP, LIME and other interpretability techniques.
  • Produce comprehensive, well-reasoned Model Validation Reports.
  • Evaluate AI/ML models, LLMs, retrieval-augmented systems, agentic workflows, and prompt-engineering methods.
  • Ensure validation standards align with Responsible AI principles including fairness, transparency, and robustness.
  • Collaborate with data scientists and model developers across business and functional teams to understand modelling intent, design rationale, and underlying assumptions.
  • Contribute to exploratory AI/ML proofofconcept (POC) initiatives to deepen technical understanding, enhance validation methods, and support innovation within DMO.

Requirements

  • Preferably a postgraduate degree in Data Science, Statistics, Mathematics, Analytics, Computer Science, or quantitative discipline.
  • At least 4 years of handson experience in model development, model validation, quantitative analytics, or AI/ML evaluation within financial institutions or similarly regulated environments.
  • Strong theoretical and practical knowledge of machine learning, AI, statistical models, and model validation techniques.
  • Strong understanding of feature engineering, feature selection, and data quality checks.
  • Proficiency in evaluating model performance and diagnostics across statistical, ML, and AI models.
  • Understanding of explainability techniques, including SHAP, LIME, and other model interpretation methods.
  • Analytical skills to identify modelling weaknesses, design flaws, and performance gaps.
  • Strong reporting skills to produce high-quality validation deliverables.
  • Familiarity with Responsible AI concepts such as fairness, transparency, and robustness.

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About Company

Job ID: 146157583

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