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Open nowPosted 5 hours ago

Desk Quant, Macro / Relative Value (RV)

Dymon Asia13 open roles

Where
Singapore
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Your applicationOpen nowDesk Quant, Macro / Relative Value (RV)Dymon Asia · Singapore

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This job: posted 5 hours ago

The posting

Job Description: Desk Quant, Macro / Relative Value (RV)

Location: Singapore

About Us

Dymon Asia Capital (“Dymon Asia”), founded in 2008, is a leading alternative investment firm with assets across public and private markets. The firm’s flagship hedge fund product is the Multi-Strategy Investment Fund (MSIF), an Asia-focused multi-manager multi-strategy fund that seeks to generate absolute consistent uncorrelated returns from emerging and developed markets.

Headquartered in Singapore, Dymon Asia operates from nine offices across the Middle East and Asia, including Hong Kong, Tokyo, Dubai, Shanghai, Mumbai, and Kuala Lumpur. Our platform is built on our people. We bring together diverse perspectives, expertise, and experience across our multi-strategy and private markets businesses. Maintaining a collaborative culture where our people are set up to do their best work is central to how we operate.

This role carries a centralized desk-quant mandate within the Front-Office Desk Quant team, delivering quant analytics for Risk, Pricing, and Quantitative Trading. The focus is on research and methodology for Macro rates and relative-value products (swaps, swaptions, IRS, curve/RV trades), developing the models, metrics, and analytical frameworks that underpin Pre-Trade analytics, in close partnership with Portfolio Managers, Traders, model quants, and developers.

Key Responsibilities

  • Develop and validate pricing and risk methodologies for Rates, FX, and RV products, including swap/swaption pricing, FX Swaps, FX Options, XCCY Basis Swaps, IRS Greeks, PnL-explain/attribution decomposition, and fixing-risk aggregation logic across index and fixing dates.
  • Research relative-value and systematic strategies, including PCA-based curve/RV analytics, factor and spread methodologies, and signal construction for the Macro and RV space.
  • Design and run back testing frameworks, building robust time-series infrastructure (including “as-of” custom time-cut logic), data-caching, and generic back testing methodology to test and validate strategies and models.
  • Investigate pricing, market-data, and PnL discrepancies at a methodological level, defining the correct calculation approach and driving fixes with model quant and developers.
  • Translate research into desk analytics by specifying the models and metrics behind rates monitors, RV scanners, and risk/PnL viewers, prototyping in Python, Excel, or Stream lit, and handing off to developers for productionisation.
  • Present methodology and findings to Portfolio Managers to support trade-idea expression and model or product changes.

Job Requirements

  • Degree in quantitative discipline such as Mathematics, Physics, or Financial Engineering; CQF, FRM certification, or a postgraduate degree in a quantitative field is advantageous.
  • 4 to 5 years of experience in a quantitative research or desk-quant role facing Front-Office teams (Portfolio Managers/Traders).
  • Strong grounding in the mathematics of Fixed Income and Rates, including curve construction, swap/swaption pricing, and the risk/Greeks of IRS and RV structures.
  • Applied statistical and quantitative-methods skillset, including PCA, time-series analysis, factor models, and the design of back tests for systematic strategies.
  • Excellent Python skills for quantitative research and modelling, with comfort building analytical libraries rather than scripts; C++/C# and Excel/VBA are a plus for rapid analytical prototyping.
  • Market-risk methodology experience, including risk measures such as VaR and PnL attribution.
  • Rigorous approach to model and methodology validation and documentation.
  • Deep knowledge of trade-idea expression and relative-value strategies in the Macro and RV space, including curve, spread, carry/roll, and cross-market RV.
  • Experience designing and running systematic-strategy testing and back testing processes end-to-end.
  • Market-data connectivity via vendor APIs such as Bloomberg or Refinitiv for research datasets.
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