Data Scientist

Must Have Technical/Functional Skills

Technical Proficiency: Strong 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.

Roles & 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

Salary Range: $90,000 to $105,000 per year

Qualifications: BACHELOR OF COMPUTER SCIENCE