Credit Risk - Senior Associate - Bangalore

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

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.

Experience level 4-7 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 or 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
• Experience in bureau data from credit unions e.g. D&B, Experian, Equifax, Transunion
• Experience in vendor models and ratings like Fitch, Credit pro, Moody etc. o Knowledge about external / benchmark models on consumer portfolios is a plus (FICO Score, Standards and Poors, Fitch or Moodys Ratings)
• Selecting, implementing and/or using commercial credit risk workflow, analytics- e.g., Moodys KMV, S&P and/or, reporting technologies- e.g., Oracle, Cognos, et al
  
  

Non-functional skill requirements: In order to succeed in PwC 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 clients 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
  
  

Educational Background: 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 PwC 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

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