Risk Lead – Proprietary Trading Desks : Listed derivatives (index & single-stock options), OTC exotics / structured products, Equity and Debt Role Summary The role is for a desk that is being setup. Candidate will be key founding member of the team. Own end-to-end market risk for a multi-strategy prop desk. Design / enforce limit frameworks, monitor intraday Greeks, run VaR / ES and stress programs, validate pricing models, and operate RMS / OMS controls with rapid incident response (kill-switch). Core Responsibilities Intraday Risk & Limits : Real-time delta / gamma / vega / theta;
algo guardrails (clocksync, stale-quote, runaway-algo). Adhere to SEBI and NSE / BSE risk / algo norms (peak margin, OTR, trade / position limits). Own RCSA, incident post-mortems, audit closure. Data & Tooling : Dashboards for Greeks, VaR / ES, stress heatmaps, limit consumption;
automate intraday P&Lexplain. Partner with Quants / Tech to validate pricers / Greeks and data pipelines;
enforce data quality (corp actions, IV surfaces, auctions, borrow / SLB). Governance & Stakeholders : Run risk forums;
publish daily risk packs;
deliver 30 / 60 / 90 control uplifts;
train traders on limithygiene, scenario discipline, margin economics. Must-Have Experience & Skills 5–8 years in market risk with 3–5 years hands-on coverage of listed options and OTC exotics / structured products on a prop or sell-side trading desk. Strong options theory (smile / skew / term), vol dynamics, scenario design, Greek aggregation, VaR / ES, and back-testing. Solid grasp of Indian market microstructure (NSE / BSE;
auctions, lot sizes, timings) and exchange / SEBI risk & algo requirements. Tooling : Python (NumPy / Pandas / SciPy), SQL, advanced Excel;
comfort with Jupyter / BIdashboards and version control (Git). (Bonus : kdb+ / q, C++ / Rust for pricer validation;
cloud for risk jobs.) Education (no licenses / certifications) Bachelor’s in Engineering (CS / EE / ME / IE) or STEM (Mathematics, Statistics, Physics, Economics), and One of : Master’s in Statistics / Applied Mathematics / Financial / Computational / Quantitative Finance / Data Science, or MBA (Finance) from a recognized institution with demonstrable derivatives / risk coursework and hands-on options exposure. Evidence of quant foundation expected : probability / statistics, time-series / econometrics, stochastic processes / Itô calculus (working intuition), numerical optimization, Monte Carlo, and PDE-based pricing methods. KPIs Zero material regulatory breaches;
limit-breach rate & time-to-contain;
VaR back-testing exceptions within policy;
incident MTTR;
model-risk findings closed on time;
% automated checks / alerts;
stability of P&L explain residuals.
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Days Left Lead • Republic Of India, IN
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