Job Description

Application Deadline: 01 April 2025 Job Description Title Senior Manager/Manager - Model Risk Department Model Risk, which is part of larger Enterprise Risk team Location Gurgaon Office / Bangalore Office Reports To Associate Director - Model Risk Level Level 6 We re proud to have been helping our clients build better financial futures for over 50 years. How have we achieved thisBy working together - and supporting each other - all over the world. So, join our Model Risk team and feel like you re part of something bigger. About your team Global Risk: The risk team in Fidelity covers the management oversight of Fidelity s risk profile including key risk frameworks, policies and procedures and oversight and challenge processes. The team partner with the businesses to ensure Fidelity manages its risk profile within defined risk appetite. The team is circa 120-strong, and growing, covering all facets of risk management including investment, operational, enterprise, and technology risk. Enterprise Risk Management (ERM): The ERM function is lead by the Head of Enterprise Risk and the primary purpose of ERM is to ensure that the business is managing risk within its agreed risk appetite, and in accordance with the associated ERM Framework. The ERM function is also responsible for capital management, 2nd line oversight of strategic and financial risks, risk regulatory reporting, risk appetite, risk culture and the ERM framework. It also acts as the oversight function for model risk and EUC Risk. The team is currently 35+ strong and is being invested in further to strengthen the function.The Model Risk team size is 12. About your role A senior model validation professional for conducting validation of investment management models and other financial models with a primary focus on AI and ML models, including advanced language models like GPT and broader Generative AI (GAI) systems. This role requires a deep understanding of AI and ML models, their underlying mathematics, and the technology used for implementation. The ideal candidate will have a strong grasp of current trends in AI and ML model usage, especially within the investment management space. Additionally, the role involves staying informed about responsible AI and ML usage and evolving regulatory expectations in different geographies. The Model Risk Manager will tackle challenges related to complex and extensive AI and ML models and innovate solutions to conduct effective model risk assessment and lead validation of AI/ML models, including client facing LLMs/chatbots and GAI used for investment research, advice and recommendations to clients. In addition, Model Risk Manager will provide qualitative SME analysis of asset management and pricing models used for asset allocation, pricing and/or risk calculations. As Senior Model Validation Quant, this role focuses on engaging with business, i.e. model owner and developers in a model validation exercise, conducting in-depth validation analyses, identifying potential issues and communicate effectively to relevant stakeholders. Facilitate knowledge sharing and effective risk management to benefit the team and the wider business. while maintaining strict adherence to FILs Model Risk Policy and procedures. Key Responsibilities To develop a strong understanding of FILs Model Risk Policy and procedures and support education efforts with internal and external stakeholders Independently lead model validation exercises, applying rigorous analysis to assess model accuracy, robustness, and compliance with FILs Model Risk Policy or other relevant regulations. Identify potential issues and discrepancies and engage in open discussions with stakeholders to reach consensus on appropriate remediation actions. Translate complex technical findings into clear and actionable recommendations for both technical and non-technical stakeholders. Act as a subject matter expert, providing guidance and insights to model owners and developers, ensuring compliance with FILs Policy and procedures. Stay abreast of current trends in AI and ML model usage and controls, especially within asset management, and apply this knowledge to model validation processes. Stay informed about evolving regulatory requirements related to AI and ML model usage in various geographies and ensure compliance in model validation. Identify and address challenges associated with large and complex AI and ML models and develop innovative solutions for effective model risk control. Implement validation frameworks for emerging technologies like Retrieval Augmented Generation (RAG) and agent-based systems. Foster a collaborative environment within the Model Risk Team, promoting knowledge sharing and teamwork. Mentor and guide junior team members in their professional development. About you Experience and Qualifications Required Solid understanding of all model types (investment, pricing, risk capital) with strong SME expertise in AI and ML models, including natural language processing (NLP), deep learning, and advanced language models. 5-10 years of experience in quantitative modelling and model validation and risk related roles within the financial industry - investment banking or asset management is preferable. Advanced degree (Ph.D. or Masters) in a quantitative field such as Mathematics, Statistics, Computer Science, or a related discipline preferred. Proficiency in programming languages commonly used in AI and ML, such as Python, TensorFlow, or PyTorch. Strong MS Excel expertise with VBA. Ability to demonstrate project delivery across model validation, model documentation will be highly advantageous. Hands-on mentality Excellent analytical, problem-solving and written skills. Strong people management skills and experience Excellent at providing innovative ideas and comfortable working under pressure Dedicated to maintaining high quality standards and client satisfaction Hands on experience building, enhancing and running model validation processes is essential. Feel rewarded