- Gurugram or Noida with Shift timing : 0200 PM to 1030 PM
- Bachelor’s/master’s in finance, Economics, Engineering, Statistics, Data Science, or related field.
- 5–8+ years of experience in Investment Analytics, Fixed Income Research, Portfolio Strategy, or Quantitative Finance.
- Strong hands‑on skills in Python, Excel (advanced), SQL, and data visualization tools (Power BI/Tableau).
- Deep understanding of fixed income markets, structured products, yield curves, and macroeconomic indicators.
- Experience with Aladdin, Empyrean, Bloomberg, or similar tools is highly desirable.
- Strong analytical, problem‑solving, and communication skills.
We are seeking a highly skilled Investment & Portfolio Analytics Specialist (Lead Business Analyst Role) to support key portfolio optimization initiatives, analytical modeling, risk assessment, data management, and reporting for multi‑asset fixed income portfolios. This role combines quantitative analysis, Python/Excel modeling, dashboard development, market surveillance, and cross‑functional collaboration to inform portfolio strategy, asset allocation, and performance evaluation. The ideal candidate will bring strong analytical rigor, technical expertise, and experience working with complex financial datasets—particularly fixed income, structured products, and macroeconomic variables.
Key Responsibilities
1. Portfolio Optimization & Enhancements
- Enhance the Existing Investment Portfolio Optimizer, including:
- Adding filters to exclude securities aligned with current investment strategy.
- Incorporating methodologies to flag securities that may be inaccurately priced.
- Ensuring optimization tools can run seamlessly in the U.S. environment (Python‑based).
- Lead Opportunity Set Optimization, including:
- Building Excel/Python optimization frameworks for scenario‑based asset allocation.
- Conducting time‑series analyses, risk‑weighted relative value assessments, and macro‑linked analytics.
- Incorporating macroeconomic variables, interest‑rate regimes, and yield curve permutations.
- Developing fair‑value models (typically regression‑based) to support portfolio decisions.
2. Dashboard Development
- Aggregate, clean, and maintain asset‑class‑level datasets supporting the surveillance process.
- Build centralized dashboards to track CUSIP‑level portfolio performance and trends.
- Expand surveillance metrics to include:
- Geographic exposures for RMBS
- CLO loan‑ and sector‑level exposures
- CMBS property‑type exposures
- Other data‑intensive structured‑products analytics
3. Portfolio & Market Data Management
- Update and maintain recurring market and portfolio datasets:
- Generic spreads (weekly)
- New issuance trends (weekly)
- Portfolio holdings, ratings changes, and SSFA‑based risk weights (monthly)
- Surveillance datasets (monthly)
- Index and generic performance metrics (monthly)
- Collaborate with LFO to compile performance data and support monthly portfolio performance reporting.
4. Risk Management & Modeling
- Support market value‑at‑risk and capital implications analysis, including proprietary scenario modeling (e.g., Aladdin Risk).
- Conduct benchmarking of cash‑flow models (Aladdin, Empyrean, Bloomberg, J.P. Morgan, etc.).
- Evaluate model differences and provide recommendations to strengthen internal modeling frameworks.
5. Regulatory & Performance Reporting
- Support periodic and regulatory reporting, including:
- Portfolio holdings
- Surveillance updates
- Monthly performance scorecards
Ensure accuracy, consistency, and timeliness of submissions.
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6. Innovation & Future‑Focused Initiatives
- Contribute to forward‑looking initiatives, including:
- Data‑architecture modernization
- AI/ML integration to enhance analytics workflows
- Proprietary modeling (prepayments, credit analytics, scenario simulation)
Recommend opportunities to streamline processes and reduce manual dependencies.
