CECL & Qual - Associate - Bangalore

A career in our Advisory Acceleration Centre is the natural extension of PwC’s leading class global delivery capabilities. We provide premium, cost effective, high quality services that support process quality and delivery capability in support for client engagements.

To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.

Responsibilities

As an Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:

• Invite and give in the moment feedback in a constructive manner.
• Share and collaborate effectively with others.
• Identify and make suggestions for improvements when problems and/or opportunities arise.
• Handle, manipulate and analyse data and information responsibly.
• Follow risk management and compliance procedures.
• Keep up-to-date with developments in area of specialism.
• Communicate confidently in a clear, concise and articulate manner - verbally and in the materials I produce.
• Build and maintain an internal and external network.
• Seek opportunities to learn about how PwC works as a global network of firms.
• Uphold the firm's code of ethics and business conduct.
  
  

Fraud/AML Risk Analytics Professional Job Specification

Candidate would be responsible for developing, validating, auditing and maintaining AI/ML/NLP models for Fraud/AML/Credit risk. Candidates would be expected to support financial institutions on meeting jurisdictional regulatory requirements and their broader risk management initiatives.

Multiple positions required;

Experience level 2-3 years of experience; Location: Bangalore

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 cloud-based 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, Self-identified 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.