Job Title:  Manager | Market Risk Quant | Hyderabad | Regulatory & Financial Risk

Manager | Regulatory, Risk & Forensic-Regulatory and Financial Risk | Market Risk

• Location:  Hyderabad
• Entity:  Deloitte Touche Tohmatsu India LLP

The team

Deloitte Strategy, Risk & Transaction helps entities mitigate risk while discovering new opportunities to create value. Our end-to-end risk services span all domains, from managing strategic risks in the C-Suite to improving board oversight, and from balancing financial and environmental policies to addressing cyber threats. Learn more about Risk, Regulatory & Forensic)

Your work

• Provide independent review and validation compliant with MRM policies and procedures of the client, regulatory guidance and industry leading practices, including evaluating conceptual soundness; reasonableness of assumptions and input reliability; implementation testing; sensitivity/scenario analysis; model suitability and comprehensiveness of performance monitoring plan. 
• Write validation documents including testing analysis & conclusions, findings, and model outcome that could be used for presentations both internally as well as externally (Regulators). 
• Verbally communicate results and debate issues, challenges and methodologies with internal audiences including senior management. 
• Represent the MRM team in interactions with regulatory and audit agencies as and when required. 
• Keep up to date of the financial markets, business trends, and regulatory guidelines (such as Basel, FRTB, IRRBB, SR 11/7, etc.) on a frequent basis to enhance the quality of Validation and related Risk Management deliverables. 
• Work across projects involving model audits, validation and development activities. Upskill in these activities as and when required. 
• Explain difficult financial modelling/valuation concepts to diverse audiences and to experts at various clients. 
• Model Lifecycle Responsibility: Experience with either model development or model validation activities, ensuring robust model design, accurate performance assessment, and compliance with risk management frameworks and regulatory standards.
• Model Development: Responsible for designing, building, and maintaining quantitative models across various domains including business forecasting, pricing, risk assessment models, AML etc. Work spans multiple asset classes and business lines, leveraging advanced mathematical techniques such as stochastic processes, optimization, and statistical inference to address complex modelling challenges.
• Model Validation: The specialist will be responsible for the independent quantitative review and rigorous challenge of all models across domains. This involves verifying conceptual soundness, assessing model assumptions, and evaluating implementation accuracy. Key activities include statistical performance testing, scenario analysis, sensitivity testing, and back-testing to ensure models meet defined risk coverage objectives and adhere to internal model risk management frameworks and regulatory expectations, while maintaining computational and operational viability.
• Ongoing Monitoring Review: Responsible for periodically substantiating the ongoing fitness of models in accordance with a model’s approved Ongoing Monitoring Plan (“OMP”). Assess model changes, model limitations, assumptions, process verification and outcomes analysis for each model. Identify trends in key metrics and provide critical analysis of model performance with respect to metric thresholds; identify threshold breaches and review documented remediation plans.
• Regulatory Compliance and Reporting: Ensure all model validation/ development activities meet regulatory standards (e.g., Basel III/IV, FRTB) and internal governance policies. Prepare clear, concise development/ validation reports and presentations for risk committees, auditors, and regulators, articulating model limitations, assumptions, and validation outcomes.

• Senior Managers would be also expected to: 
  • Mentor junior professionals within the organization. 

• Review and provide feedback on the tasks completed by junior professionals. 
• Develop material on topics related to financial concepts, regulations, etc., and conduct internal/external training sessions on the same. 

Key skills required: 

• Minimum 5-8 years of relevant experience in working with model validation, model development.
• Knowledge of Basel III, IV.
• Strong knowledge of Market Risk Concepts and metrics (VaR/Value at Risk, Risk Sensitivities, FRTB, IRRB and Market Risk Quant)
• Basel, SAS, Reg Reporting and System implementation.
• Valuation and Independent Price Verification
• Knowledge on Regulatory banking risk management guidelines, risk management practices
• Understanding of market risk infrastructure (Market Risk/Model Risk), Knowledge of SQL, R, Python, VBA etc.
• Background in mathematical finance with a master’s degree in financial engineering or quantitative finance. Advanced degree like a PhD in a related field is a plus. Candidates with a strong academic background but without a master's degree may also be considered. 
• A bachelor's degree in Statistics, Mathematics, Physics, Computer Science or Engineering is essential. 
• Relevant professional certifications like CQF, CFA, FRM or progress towards it are preferred. 
• Experience in a Quant role in Validation and/or Development of models in a financial institution and/or Consulting/Advisory firm.  
• Experience in any of the following model types: Market Risk, Liquidity Risk, Counterparty Credit Risk, Capital Risk, Credit Risk, Finance & Treasury, Financial Crime, or Data Science is essential.  
• Background in derivative finance with basic understanding of stochastic calculus and numerical techniques for derivatives pricing (Monte Carlo / Finite Difference). 
• Working knowledge of statistical techniques and quantitative finance is essential. Good understanding of various complex financial instruments is preferred. 
• Knowledge of popular machine learning techniques is preferred. 
• Strong written & verbal communication skills with ability to present to internal and external stakeholders. 
• Proficient programmer in any of the languages such as Python, R, SAS, etc.  
• Willingness to learn new and complex topics and adapt oneself as per the client needs.