Associate - Data Science - Model Validation - BFS - IIM/IIT/NIT/ISI

- Communicate with modeling teams to understand their models and intended use

- Help teams write documentation covering model methodology, data and performance

- Review and challenge models on conceptual soundness, assumptions and limitations, data, developmental evidence in support of modeling choices, performance, implementation and documentation

- Understand the core methodology in solutions and the context in which it will be deployed so as to find risks/gaps

- Communicate with Model Risk Management group to understand and address Bank's risk management needs

- Develop efficient methodologies to detect and to quantify risks/gaps in modeling solutions, especially AI/ML

- Monitor metrics for out-of-tolerance breaches

- Look for unexpected risks / unintended consequences of an AI solution over its life cycle

- May oversee work of junior team members in same area of focus

Requirements:

 Education:

- Masters/Bachelors degree in a quantitative field such as Mathematics, Physics, Finance, Engineering or Statistics from one of the premier institutes like ISIs/IIMs/IITs/NITs etc.

- Candidates must have any of financial certifications like CFA, FRM (at least level 1/part 1 should have been cleared).

- Hands-on experience with Statistical Modeling/Machine Learning/Deep Learning techniques is must.

- Well-versed in programming languages like R/Python/SAS and be familiar with Deep Learning Frameworks like Tensorflow/Pytorch.

- Knowledge of financial instruments and financial risk/operational model risk management principles is must.

- Ability to understand and implement techniques discussed in AI research papers (academic and technical).

Desired Skills: 

- Understanding of the financial industry including risk and regulatory environment desired.

- Able to communicate effectively and work well with the existing team.

- Work in high pressure environment and with attention to detail

- Team player