VP - Talent Aquisition at Peepal Consulting
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Credit Risk Analytics Role - BFS (2-12 yrs)
One of the most prestigious professional services firm in the world, serving as the auditor to nearly half of the world's largest banks. Risk and Regulatory (R&R) comprises of a highly experienced team of risk management specialists supporting global financial institutions in their risk management initiatives. R&R has significant exposure to, and driver of, industry leading practices and has deep knowledge of regulatory expectations. R&R professional's experience covers all financial model types, including those used to manage credit risk, market risk, operational risk and compliance risk- as well as those used for financial reporting, valuations and economic capital estimation.
Risk Analytics Center of Excellence (CoE), is the India extension of R&R practice and provides key risk analytics services to global banks, investment firms, and asset management entities. It comprises of risk analytics professionals with stellar quantitative pedigree from premier institutions, industry certifications in CFA, FRM, PRM etc. and proven professional credentials in risk modeling and analytics at reputed financial institutions and consulting firms. As an integral part of team R&R, Risk Analytics CoE drives risk analytics engagements, opportunity pursuits and cutting edge innovation using data science, Artificial Intelligence, Machine Learning and Deep Learning.
Credit Risk Analytics Professional Job Specification :
- Candidate would be responsible for developing, validating, auditing and maintaining credit risk models. Candidates would be expected to support financial institutions on meeting jurisdictional regulatory requirements and their broader risk management initiatives.
Multiple positions required :
Experience level : 2-12 years of experience;
Location : Bangalore
Core Skill Requirements :
- Candidate must have relevant experience in in statistical / mathematical modeling, quantitative research, credit risk management, or related field at a reputed bank, investment or broker services, asset management firm, Insurance provider or a consulting firm.
Wider skill requirements include :
- Experience in Credit Risk Modeling PD/LGD/EAD - TTC, PIT, Stressed and unstressed portfolio
- Experience in Model Development, Model Validation, Model Audit (implementation and execution experience will not be considered directly relevant)
- Knowledge of one or more of global regulatory norms - CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR-11/7, E-23 around data sufficiency, modeling methods, industry standards etc.
- Well versed with one of more statistical techniques used in credit risk modeling - Logistic Regression, Time series, OLS, Probit models, Survival techniques, Tobit, Fractional Logistic, Beta model, State Transition Matrix, Single Factor Merton model etc.
- Experience in Machine learning algorithms like Random Forest, SVM, Neural Network etc. and Artificial Learning use cases such as Natural Language Processing, Robotics etc. will be a plus
- Proficiency in one or more analytical tools such as SAS, R, Python, Matlab, Scala, VBA etc. Experience in Data Science and cloud based analytics platform will be a plus
- Understanding of credit risk metrics like RWA, Expected loss, Regulatory and Economic capital, OTTI, Watchlist, Asset quality etc.
- Conceptual understanding of the data and methodology used for credit risk regulatory models
- Leveraging experiential know-how of a wide range of loan types, including C&I, CRE, RRE, ABL, Leasing, Credit Card, Vehicle, Personal etc.
- Prior experience in domains like commercial banking, retail banking, treasury, investment management and strong knowledge of risk data analysis and development, strategy design and delivery deployment.
- Vendor Experience :
a. Experience in bureau data from credit unions e.g. D&B, Experian, Equifax, Transunion
b. Experience in vendor models and ratings like Fitch, Credit pro, Moody etc.
c. Knowledge about external / benchmark models on consumer portfolios is a plus (FICO Score, Standards and Poor's, Fitch or Moody's Ratings)
d. Selecting, implementing and/or using commercial credit risk workflow, analytics- e.g., Moody's KMV, S&P and/or, reporting technologies- e.g., Oracle, Cognos, et al.
Non-functional skill requirements :
In order to succeed in Risk CoE, it is desirable for candidates to possess :
- Understanding of market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client's business
- Excellent oral and written communication skills
- Solid analytical and problem-solving skills; ability to isolate and solve issues using large amounts of data
- Process orientation with strong technical skills and attention to detail
- Deep technical capabilities and industry knowledge of financial products
- Willingness to travel to meet client needs, as needed
- Desired candidate must have a master's degree or higher in a quantitative discipline such as Economics, Statistics, Mathematics, Operation Research, Econometrics, Data Science, Finance, Engineering + MBA; advanced degree is a plus; Industry relevant certifications in CQF, FRM, CFA, CPA certification is a plus
Additional Requirement for Senior Positions :
Candidates aspirant of senior positions at Risk CoE are expected to possess :
- Proven consulting skills to structure vague problems at hand and conceptualizing solutions
- Credentials in leading and driving large and or complex risk analytics engagements and initiatives independently
- Experience in supporting sales pursuits for risk analytics offerings and solutions
- Ability to manage multiple engagements simultaneously along with leading people and initiatives
- Strong conceptual understanding of various functional/technical skills
- Ability to drive innovation and thought leadership in the risk management domain
- Intellectual property, patents and exclusive rights on any innovative solution is a plus