Manager - Risk Analytics - Consulting Firm

Engagement Execution:

- Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation and end-to-end delivery of risk solutions for the clients.

- Ability to manage workstream of large projects / small projects with responsibilities of managing quality of deliverables for junior team members.

- Demonstrated ability of managing day to day interactions with the Client stakeholders

- Practice Enablement

- Guide junior team members.

- Support development of the Practice by driving innovations, initiatives.

- Develop thought capital and disseminate information around current and emerging trends in Risk.

Required skills and experience :

- 7 - 12 years of relevant Risk Analytics experience at one or more Financial Services firms, or Professional Services / Risk Advisory with significant exposure to one or more of the following areas:

Development, validation, and audit of:

- Credit Risk- PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting and Revenue Forecasting Models, IFRS9/CECL Loss Forecasting Models across Retail and Commercial portfolios

- Credit Acquisition/Behavior/Collections/Recovery Modeling and Strategies, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios

- Regulatory Capital and Economic Capital Models

Liquidity Risk - Liquidity models, stress testing models, Basel Liquidity reporting standards . Anti Money Laundering - AML scenarios/alerts, Network Analysis

Operational risk - AMA modeling, operational risk reporting. Conceptual understanding of Basel/CCAR/DFAST/CECL/IFRS9 and other risk regulations

- Experience in conceptualizing and creating risk reporting and dashboarding solutions.

- Experience in modeling with statistical techniques such as - linear regression, logistic regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time series - ARMA/ARIMA, ML interpretability and bias algorithms etc.

- Programing Languages - SAS, R, Python, Spark, Scala etc., Tools such as Tableau, QlikView, PowerBI, SAS VA etc.

- Strong understanding of Risk function and ability to apply them in client discussions and project implementation.

Academic Requirements:

- Master's degree in a quantitative discipline mathematics, statistics, economics, financial engineering, operations research or related field or MBA from top-tier universities.

- Strong academic credentials and publications, if applicable.

- Industry certifications such as FRM, PRM, CFA preferred.

- Excellent communication and interpersonal skills.