Private Equity Portfolio Credit Risk And SAS Analytics Modeler

What role will you play in the team

You will act as an essential quantitative risk specialist within our private equity portfolio management division stationed in Coimbatore. Your core mandate will be to design, implement, and monitor sophisticated credit risk evaluation frameworks, default probability models, and portfolio stress-testing suites across our diverse private equity investments. You will collaborate closely with portfolio operations teams and risk committees to safeguard capital assets against macroeconomic shocks and idiosyncratic portfolio company vulnerabilities.

What you will do

Your daily responsibilities will center on developing statistical risk models, executing quantitative stress tests, and analyzing credit risk indicators using specialized software platforms. You will evaluate counterparty exposures, monitor debt service coverage ratios across portfolio entities, and generate predictive default analytics. Additionally, you will formulate quantitative risk mitigation strategies and author detailed risk assessment reports for our investment committee and institutional limited partners.

Key responsibility

• Develop and calibrate advanced statistical credit risk models and probability of default algorithms using SAS Risk Management and Risk Management Software.
• Execute comprehensive portfolio stress-testing simulations incorporating severe macroeconomic downturns, interest rate hikes, and liquidity squeeze scenarios.
• Analyze financial statements, cash flow statements, and balance sheet metrics of portfolio companies to identify early warning signals of financial distress.
• Integrate quantitative data streams from Bloomberg Terminal and FactSet into internal risk dashboards to monitor industry-specific credit spreads and default rates.
• Collaborate with portfolio company CFOs to establish rigorous internal controls, working capital benchmarks, and treasury risk management protocols.
• Prepare comprehensive risk reporting packs, quantitative analytics decks, and compliance certificates for regulatory bodies and investment board reviews.

Required Qualification and Skills

• Bachelor’s or Master’s degree in Quantitative Finance, Statistics, Actuarial Science, Financial Engineering, or a related analytical discipline.
• Demonstrated proficiency in SAS Risk Management, Risk Management Software, Financial Analysis, and statistical modeling tools.
• Strong working knowledge of data extraction and market intelligence platforms such as Bloomberg Terminal, FactSet, and Eikon.
• Between 1 to 2 years of specialized professional experience in credit risk modeling, quantitative portfolio analytics, or risk advisory within financial services.
• Exceptional analytical acumen, programming capability in statistical languages, and meticulous attention to data integrity and model validation standards.
• Excellent interpersonal skills with the ability to communicate technical risk metrics clearly to non-financial stakeholders and executive leadership.

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Benefits Included

• Attractive annual remuneration package complemented by performance-driven quarterly bonuses and annual retention incentives.
• Robust health and wellness insurance plans covering hospitalisation, outpatient care, and preventive health check-ups.
• Dedicated learning and development budget for acquiring advanced risk management certifications, FRM credentials, and SAS programming badges.
• Flexible paid time off program including earned leaves, sick leaves, and sabbatical options for continuous professional rejuvenation.
• Collaborative, data-driven work environment equipped with cutting-edge analytical hardware, multi-screen setups, and ergonomic workstations.
• Comprehensive corporate benefits package featuring meal vouchers, transportation allowances, and regular team-building engagements.

A Day in the Life

Your morning kicks off with analyzing overnight credit spread movements across high-yield corporate debt indices using Bloomberg Terminal and Risk Management Software. You spend mid-morning running SAS-based econometric simulations to assess the resilience of a manufacturing portfolio company against commodity price volatility. After reviewing the simulation outputs, you draft an analytical risk advisory note for the investment committee. The afternoon involves coordinating with the portfolio valuation team to reconcile credit risk adjustments with fair market value assessments.