Quantitative Analyst

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 alanguage that institutional investors and rating agencies understand. You will be the primary architect ofthe Swap Analysis and Investor Impact Assessments required to move our internal and externalportfolios 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 marketliquidity (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-BackedSecurities (ABS) shelf registrations and private placements. Pool Performance Modeling: Forecast the cash-flow behavior (CPR, CDR) of loan pools underthe new CIU decisioning framework. 2. Business Impact & Swap Analysis Strategic Sizing: Conduct exhaustive Swap Analysis on historical data to quantify the impact ofthe new BA Score on portfolio yield and loss rates. Capital Optimization: Determine the optimal Pricing vs. Risk matrix to ensure the internal bankmaximizes Return on Capital (ROC) while meeting SaaS client benchmarks. Scenario Stress Testing: Build Monte Carlo simulations to show investors how the new modelsperform 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 thatprove 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 cashflow engines). Domain Knowledge: Understanding of Credit Ratings methodologies