S&C Global Network - AI - CFO & EV - Risk Analytics - Senior Manager

Management Level: Ind & Func AI Decision Science Senior Manager

Location: Gurgaon,Bangalore
Must-have skills: Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques: Linear Regression, Logistic Regression, GLM, GBM, XGBoost, Time Series (ARMA/ARIMA), Programming Languages: SAS, R, Python, Spark, Scala, Tools: Tableau, PowerBI, Regulatory Knowledge: Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions
Good to have skills: Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms

Job Summary

We are seeking a highly skilled Ind & Func AI Decision Science Consultant to join the Accenture Strategy & Consulting team in the Global Network – Data & AI practice. You will be responsible for risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role offers opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation.

Roles & Responsibilities:

Engagement Execution

• Lead client engagements that may involve model development, validation, governance, risk strategy, transformation, implementation, and end-to-end delivery of risk management solutions for Accenture’s clients.
• Advise clients on a wide range of Credit, Market, and Operational Risk and Management/Analytics initiatives. Projects may involve Risk Management advisory work for CROs, CFOs, etc., to achieve a variety of business, operational, and regulatory outcomes.
• Be a trusted advisor to senior executives and management on their business needs and issues.
• Develop and frame a Proof of Concept for key clients, where applicable, including scoping, staffing, engagement setup, and execution.

Practice Enablement

• Mentor, groom, and counsel analysts, consultants, and managers to be successful and effective Management Consultants.
• Support development of the Risk Analytics Practice by driving initiatives around staffing, quality management, recruitment, capability development, knowledge management, etc.
• Develop thought capital and disseminate information around current and emerging trends in Financial Risk Management. Contribute to development of Accenture Points-of-View on a variety of risk analytics topics.
• Publish research and present ideas at industry conferences and seminars.

Opportunity Development

• Identify business development opportunities for our Risk Management offerings in the Banking and Capital Market domains. Develop compelling business case/response to new business opportunities.
• Work with deal teams to provide subject matter expertise on credit, market, and operational risk-related topics and participate in development of client proposals and RFP responses.

Client Relationship Development

• Develop trusted relationships with internal and external clients and have an eye for qualifying potential opportunities and negotiating complex deals.
• Build strong relationships with global Accenture Analytics and Risk Management teams, and further develop existing relationships based on mutual benefit and synergies.

Professional & Technical Skills:

• 11-15 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services/Risk Advisory with significant exposure to:
  • Credit Risk: Risk Ratings, Credit Risk Methodology, PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios.
  • Market Risk: Stress Testing, Liquidity Risk, Counterparty Credit Risk, PPNR/Revenue/Loss Forecasting, Pricing.
  • Operational Risk: Fraud Risk, Collections and Recovery, Credit Policy and Limit Management, Fraud Risk, Counterparty Credit Risk.
  • Regulatory Knowledge: Basel II/III, Solvency, FRTB, CCAR, IFRS9/CECL, etc.
• Strong understanding of banking products across retail and wholesale asset classes, and expertise in frameworks and methodologies used in risk analytics for banking portfolios.
• Expertise in risk strategy design and supporting analytics for banking portfolios.

Modeling Techniques:

• Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms.

Programming Languages & Tools:

• SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA, Moody’s Risk Calc, Bloomberg, Murex, QRM.

Additional Information:

• Master’s degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities.
• Industry Certifications: FRM, PRM, CFA preferred.
• Excellent Communication and Interpersonal Skills.
• Willingness to travel up to 40% of the time.

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