Job Description: DS Jr role- Quant (Capital Markets & Investor Strategy)
Location: Noida/Pune
Experience: 4+ Years
Role Overview
- As a Capital Markets Quant, your mission is to translate our advanced AI/ML credit engines into a
- language that institutional investors and rating agencies understand. You will be the primary architect of
- the Swap Analysis and Investor Impact Assessments required to move our internal and external
- portfolios from legacy underwriting to our new Central Intelligence Utility (CIU).
- You will ensure that our Buy-Box is optimized for both origination growth and secondary market
- liquidity (ABS/Securitization).
Key Responsibilities
1. Investor Analysis & Buy-Box Design
- Investor Sensitivity Mapping: Analyze how changes in the PD Model and Policy Overlays (e.g.,
- DSCR, Industry Risk) impact investor Buy-Boxes.
- ABS Structuring Support: Provide the quantitative backtesting required for Asset-Backed
- Securities (ABS) shelf registrations and private placements.
- Pool Performance Modeling: Forecast the cash-flow behavior (CPR, CDR) of loan pools under
- the new CIU decisioning framework.
2. Business Impact & Swap Analysis
- Strategic Sizing: Conduct exhaustive Swap Analysis on historical data to quantify the impact of
- the new BA Score on portfolio yield and loss rates.
- Capital Optimization: Determine the optimal Pricing vs. Risk matrix to ensure the internal bank
- maximizes Return on Capital (ROC) while meeting SaaS client benchmarks.
- Scenario Stress Testing: Build Monte Carlo simulations to show investors how the new models
- perform in various macroeconomic downturns.
3. External SaaS & RFP Support
- Institutional Credibility: Act as the technical liaison for SaaS clients Capital Markets teams,
- helping them justify the use of our AI-driven Buy-Box to their own funders.
- Technical Writing: Draft the Investor Methodology sections of RFPs and whitepapers that
- prove the superiority of our data-driven decisioning.
Required Qualifications
• Education: Masters/PhD in Mathematics, Quantitative Finance, or Physics. CFA or FRM
designation is a significant plus.
• Experience: 4+ years in Capital Markets, Securitization, or Credit Risk Strategy. Experience with
Fixed Income or Warehouse Lending is critical.
• Technical Stack:
- High proficiency in Python (NumPy, SciPy, Statsmodels) or R or SAS.
- Expertise in SQL for handling large-scale historical loan datasets.
- Experience with financial modeling tools (e.g., Bloomberg, Intex, or proprietary cash
- flow engines).
- Domain Knowledge: Understanding of Credit Ratings methodologies
