Gen AI Credit Risk - Senior Associate - Bangalore

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Risk Architecture

Management Level

Senior Associate

Job Description & Summary

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 datadriven decisionmaking. 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 isnt clear you ask questions and you use these moments as opportunities to grow.

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

AI/ML & Credit Risk Analytics Professional Job Specification:
Candidate would be responsible for developing validating auditing and maintaining AI/MLpowered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives.
Multiple positions required;
Experience level: 26 years of relevant experience
Location: Bangalore

Role Overview
We are looking for highcaliber professionals with strong foundations in credit risk modeling and handson experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models while also applying machine learning and generative AI techniques to enhance model accuracy efficiency and interpretability.

Key Responsibilities

• Develop validate and document credit risk models (PD LGD EAD) for retail and wholesale portfolios across regulatory (CECL IFRS 9 Basel) and businessuse contexts.
• Apply AI/ML algorithms (e.g. LightGBM XGBoost Random Forest Neural Networks) to improve prediction power and model performance beyond traditional approaches.
• Implement Generative AI and LLMbased applications using RAG pipelines document intelligence and model documentation automation. Experience with agentic frameworks like Autogen LangChain or similar would be helpful.
• Experience of development and deployment of models in cloudbased platforms such as Azure AWS GCP etc.
• Design explainable AI solutions by incorporating techniques like SHAP LIME and feature attribution methods to enhance transparency in highstakes modeling environments.
• Partner with crossfunctional teams including business stakeholders technology teams and model governance to ensure model alignment with business objectives and regulatory expectations.
• Contribute to innovation initiatives and support proposal development thought leadership and solution architecture in the AI/ML space.

Required Skills & Experience

• 26 years of total experience with minimum 2 years in AI/ML or GenAI model development or validation.
• Strong understanding of credit risk modeling frameworks scorecard development and risk metrics (e.g. RWA Expected Loss Economic Capital).
• Proficient in Python and SQL with handson experience using ML libraries such as scikitlearn Tensorflow Pytorch and transformerbased LLM packages
• Familiarity with regulatory standards such as CECL IFRS 9 CCAR/DFAST Basel II/III SR 117 and model governance best practices.
• Exposure to cloud environments (Azure preferred) version control (Git) and workflow automation tools.
• Experience with credit bureau data vendor models (e.g. FICO Moodys S&P) and financial benchmarking is a plus.
• Ability to clearly communicate complex technical content to nontechnical stakeholders through reports dashboards and presentations.

Education & Certifications

• Masters degree or higher in Statistics Mathematics Economics Data Science Engineering or Finance.
• Professional certifications such as FRM CFA CQF or in product management equivalent are preferred.
• Contributions to opensource AI / ML projects and competitions is preferred

Education (if blank degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank certifications not specified)

Required Skills

Optional Skills

Accepting Feedback Accepting Feedback Active Listening Algorithm Development Alteryx (Automation Platform) Analytical Thinking Analytic Research Big Data Business Data Analytics Communication Complex Data Analysis Conducting Research Creativity Customer Analysis Customer Needs Analysis Dashboard Creation Data Analysis Data Analysis Software Data Collection DataDriven Insights Data Integration Data Integrity Data Mining Data Modeling Data Pipeline 38 more

Desired Languages (If blank desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship

No

Government Clearance Required

No

Job Posting End Date