Model Validation - Analytics - Risk

Job Purpose: The person's primary responsibility will be end-to-end Validation of AI/ML models used in different AL/ML solutions across different functions that may include decision trees, regression models, AI/ML techniques.

· As a part of centralised team, the candidate will be responsible to validate the AI ML model across different business functions and enhance skills to adopt with the cutting-edge technology to validate the models of varying materiality and drive the detailed validation of said models as required.

· Enhance internal risk model and supervise & contribute on new risk model development project.

· Collaborate within deferent sub team within risk research whenever required.

Job Responsibilities (JR)

Actionable (4-6)

Model Building and Validation

· The candidate would be required to carry out end-to-end validation of models related to AI/ ML solutions including the review of the model assumptions, evaluation of the accuracy of models from qualitative and quantitative standpoint, and summarizing the findings in a report

· Candidate would also be expected to evaluate the adequacy of theoretical framework and model design. Conduct research as required and provide supporting materials (white papers/ RBI/EBA publications) to either support or reject a modelling framework

· Conduct replication of model results to confirm accuracy of model code and processing accuracy and capacity

· Conduct review of SAS, Python or R codes and write new codes for statistical tests and/or design new tests if necessary

· Conduct sensitivity and back testing analysis. The sensitivity analysis would include sensitivity of model results to changes in parameters and data inputs

· Assess limitations of model results for its intended use and adequacy of model documentation

· Prepare model validation report summarizing findings and providing recommendations

· Automate the structured processes to avoid manual efforts and streamline execution

· Responding to RBI on any queries related to model validation and putting requisite process / controls in place

· Depending on the seniority mentor junior members in the team on various aspects related to model building, model validation

Educational Qualifications (examples listed below)

Key Skills (examples listed below)

Post-graduate degree (preferably in Statistics, Mathematics or Quantitative Economics degree with a strong analytical skill) from a respected institution.

Minimum Experience of 5-10 Years with at least 1-2 years in relevant field.
• Good understanding of Banking especially retail assets

· Should be able to manage and groom the team assigned to him / her to develop their competencies.

· Strong understanding of model validation/development framework

· Experience with tools like Python, SAS, SQL, R etc.

· Strong Interpersonal / Communication skills

· Candidate should have sound knowledge on topics like Multivariate Statistics, Econometrics Analysis, Decision Tress (like CART, CHAID, etc.).

· Excellent Quantitative and analytical skills

Experience Required (examples listed below)

· 3-10 years of experience of working in risk modeling or Analytics with at least 1-2 years’ experience in AI ML model validation or model development
• Exposure to banking/Analytics agencies/Big4 preferable

Major Stakeholders (intra team and cross functional stakeholders, who would need to be interacted with for discharging duties) (examples listed below)

· Credit Analytics Team

· Credit Underwriting Team

· Customer Service Management

· Marketing Team

· Digital Product Management

· Risk Management Team

· Operations Team

· Data Governance team

· Policy Team

· IT Team

· Audit Team