Investment Risk Analyst AO

Location: Pune, India Experience: 3–10 Years

Join a premier global buy-side firm within our Investment Risk function. This role is a strategic partnership position where you will work alongside senior Risk Managers, Portfolio Managers, and Investment Teams to measure, monitor, and interpret risk across diverse, multi-asset portfolios.

We are looking for a high-potential individual with a strong quantitative foundation and technical fluency who aspires to evolve into a seasoned Risk Manager. Your first year will focus on mastering the "engine" of risk—building robust analytics, perfecting data pipelines, and conducting rigorous daily surveillance—before expanding into deep-dive research and strategic portfolio challenge.

1. Risk Reporting & Production Analytics

• Design & Scale: Build and maintain sophisticated risk dashboards covering factor exposures, volatility/correlation matrices, stress testing, and tail risk indicators.

• Engineering Excellence: Implement scalable, modular Python code and SQL workflows to ensure reporting is repeatable, configuration-driven, and highly robust.

• Validation: Assist with back-testing, sensitivity analysis, and benchmarking, ensuring all model assumptions and limitations are clearly documented.

2. Risk Surveillance & Exception Monitoring

• Daily Triage: Conduct daily surveillance to identify material shifts in leverage, liquidity, concentration, and factor tilts.

• Root Cause Analysis: Investigate whether changes are driven by market volatility, active positioning, or model/input drift, escalating notable findings with clear evidence.

3. Quantitative Risk Analysis & Research

• Bespoke Research: Conduct analytical deep-dives on position sizing, hedging effectiveness, and risk premia.

• Derivative Expertise: Quantify payoff characteristics, convexity risks, and liquidity constraints for structured products and derivative strategies.

• Model Benchmarking: Support model validation by stress-testing assumptions and benchmarking results against alternative risk engines.

4. PM Engagement & Communication

• Translate & Interpret: Convert complex model outputs into "investment language," helping PMs distinguish between market noise and actionable risk signals.

• Constructive Challenge: Provide evidence-based perspectives to investment teams, contributing to discussions on risk budgeting and concentration reduction.

Education & Experience

• Experience: 3–10 years of relevant experience in asset management or a sophisticated financial services environment.

• Education: Bachelor’s or Master’s degree in a highly quantitative field (Mathematics, Physics, Engineering, Computer Science, Econometrics, or Quantitative Finance).

Technical Proficiencies

• Advanced Python: Ability to write clean, maintainable, and production-ready analytical code (Pandas, Numpy, etc.).

• Expert SQL: Mastery of joins, window functions, and performance tuning for large-scale datasets.

• Generative AI: Proficiency in using LLMs to amplify productivity and refine communication. Familiarity with MCP or LLM APIs is a plus.

Quantitative & Domain Knowledge

• Risk Foundations: Strong intuition for probability, statistics, and time-series analysis.

• Portfolio Concepts: Exposure to Multi-Factor Models, VaR/ES, Duration/Convexity, Spread Risk, and Stress Testing.

• Data Discipline: A meticulous approach to handling outliers, missing data, and model limitations.

Preferred Tools (Helpful but not required)

• Familiarity with risk engines such as MSCI Barra, Bloomberg PORT, Axioma, Omega Point, or FactSet.

This is not a "back-office" reporting role. It is a high-visibility career track designed for an analytical professional who wants to be at the intersection of data science and global macro investing. You will have the autonomy to build modern tools while receiving mentorship from leading global risk professionals.