Credit Risk - Senior Associate - Bangalore

PwC is one of the most prestigious professional services firm in the world, serving as the auditor to nearly half of the world s largest banks. PwC US 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 PwC US R&R, Risk Analytics CoE drives risk analytics engagements, opportunity pursuits and cuttingedge innovation using data science, Artificial Intelligence, Machine Learning and Deep Learning. Core Skill Requirements

• Candidate must have relevant experience in Machine Learning/Artificial Intelligence, Natural Language Programming, Statistical / Mathematical modeling, quantitative research, Fraud/AML risk management, or related Credit Risk field at a reputed bank, fintech, or a consulting firm. Wider skill requirements include
• Experience in Machine learning algorithms like Random Forest, SVM, Neural Network etc and Artificial Learning use cases such as Natural Language Processing, Robotics etc AML Scenario development, enhancement. Initial threshold setting and tuning.
• Proficiency in one or more analytical tools such Python, PY Spark, Data Science and cloudbased analytics etc
• Experience in Model Development, Model Validation, Model Audit (implementation and execution experience will not be considered directly relevant)
• Business knowledge in transaction monitoring system, sanction screening, trade surveillance. Supports and/or runs global/regional internal SMEs; responsible for investigating and researching the Financial Crimes processes and tools identifying efficiency and effectiveness opportunities.
• Strengthen AML knowledge, Process Governance & Controls. Support Regulatory exams, Internal Audit, Compliance Assurance test, Selfidentified issues / findings. Identify, assess, actively manage and control the risks that could come from our business, operational and organizational decisions.
• Develop and leverage innovative features and algorithms to drive down false positives and identify perceived threat across the firm
• Utilize traditional statistical analytics, graph theory / network science, ensemble methods and the like Natural language processing, text analytics, factors analysis / construct development and testing, machine learning feature development and engineering, etc
• Prior experience in domains like AML/ Financial Crime analytics and strong knowledge of fraud data analysis and development, strategy design and delivery deployment.

Nonfunctional skill requirements

• 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 problemsolving 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