Required Qualifications & Skills:

- Technical Proficiency: Robust coding skills in languages like Python, and SQL; experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Statistical Expertise: Deep understanding of statistical modeling, probability, and advanced mathematical concepts.
- Domain Knowledge: Understanding of financial regulations (e.g., SR 11-7, CECL, CCAR) if working in banking.
- Soft Skills: Excellent technical writing and stakeholder communication; the ability to explain complex quantitative risks to non-technical business partners and legal/compliance teams.

Experience: Typically requires 7+ overall and 3-5+ years of experience in data science, risk management, or quantitative analysis

Key Responsibilities:

- Model Validation: Conduct independent reviews and testing of quantitative models, including design approach, sampling approach, sensitivity analysis, and robustness checks.
- Risk Assessment:



Assess models for conceptual soundness, data limitations, and quantitative biases (e.g., fairness and ethical AI standards).
- Compliance & Governance: Ensure all modeling lifecycles align with internal MRM frameworks and regulatory mandates.
- Effective Challenge: Provide constructive, actionable feedback and challenges to model developers regarding model design and limitations.
- Documentation: Author comprehensive validation reports and maintain documentation for audit purposes and senior management review

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data scientists (Mumbai)
🏢 SSD Shared Services
📍 Mumbai