Quant Support

About the role (Rotational Shift)

Front-line analyst on the cockpit's Exception Monitor, working the Gate 2 queue: every business quality exception, linked to itsworkflow and the specific curve or surface that failed, ranked by severity. You investigate anomalies on real market data treasuryand swap curves, CDS and CDX, equity dividends and vol surfaces, repo and FX vol and resolve each one to a clear outcome.The work builds genuine markets expertise: you learn how rate curves behave, what a suspicious 5-year-pillar move looks like, whya forward repricing test breaches, and how a fund decides data is fit for trading.

Key responsibilities

• Execute the pre-agreed remediation for each case confirm an auto-removed outlier, retain-and-notify, trigger the t1 fall backpublication, or hold the entity and escalate to the quant on pager duty — then re-validate and document the audit trail for sign-offng failures.

• Execute the pre-agreed remediation for each case — confirm an auto-removed outlier, retain-and-notify, trigger the t1 fall back publication, or hold the entity and escalate to the quant on pager duty — then re-validate and document the audit trail for sign-offng failures.

.• Run start-of-day and end-of-day content checks on schedule across intra-day, 15-minute and EoD workflows; ensure accuracy of large analytical datasets ahead of delivery deadlines.

• Spot recurring exception patterns and propose threshold or methodology improvements; build small Python/SQL checks on Databricks that reduce manual review

.• Coordinate cross-stream with production engineers when a content break traces back to a pipeline or feed issue; keep shifth and offs crisp

.Required skills & experience

• Solid grounding in finance fundamentals: time value of money, bond pricing, yield curves, duration; genuine interest in fixed

income and derivatives.

• Strong quantitative aptitude and attention to detail; comfort with statistics (distributions, outliers, standard deviations).

• Working SQL and basic Python (pandas) for data investigation; Excel fluency.

• Clear written English for exception documentation; dependable on rotating shifts including weekend coverage.

Preferred

• Exposure to market or reference data, risk analytics or performance reporting (internship acceptable); CFA Level 1 candidacy;

Databricks or any analytics-platform familiarity.

Profile

B.Tech + MBA (Finance) or MS Finance strongly preferred; strong B.Com/BSc (Math/Stats/Eco) with demonstrable marketsinterest also considered.

Curious, precise, accountable — someone who wants to understand why a curve moved, not just closethe ticket.