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Quant Trading Intern

Fasanara London, United Kingdom
Posted 1 day ago Temporary Competitive

Quant Trading Intern

Fasanara London, United Kingdom
Quant Trading Intern
Fasanara is a $6.5 billion investment group with a team of more than 130 professionals, built around the conviction that technology and data, applied rigorously, produce a structural edge in financial markets. Fasanara Digital is our dedicated digital-asset investment team, applying the same scientific, technology-led discipline to crypto markets that Fasanara has applied across private credit and fintech. The team operates a proprietary, globally distributed trading platform, capturing opportunities across more than fifteen digital-asset venues on a twenty-four-hour basis, and manages a portfolio of fully delta-neutral strategies engineered for consistent, risk-adjusted returns independent of market direction. Technology is not a support function at Fasanara Digital; it is the mechanism through which the strategy is expressed. Our execution systems, research infrastructure, and risk tooling are designed and maintained in-house, by the same people who trade on them, and every member of the desk is expected to engage directly with that stack.

We are opening a small, off-cycle internship cohort - two positions, available for immediate start for candidates who combine outstanding quantitative reasoning with strong software engineering ability. This is not a scheduled seasonal program; we are hiring now, for candidates who can begin now.

THE ROLE:
Interns are integrated directly into the desk and are held to the same standard of rigor as full-time staff, within a scope appropriate to an internship. Each intern is paired with a trader or researcher for the duration of the placement and is given ownership of a genuine research question tied to a live strategy - not an isolated academic exercise. Work progresses through the full lifecycle we use internally: hypothesis, data analysis, backtesting under realistic constraints, peer review, and, where the result warrants it, a path toward production.

KEY RESPONSIBILITIES
  • Analyse live and historical market data - order books, funding rates, basis, venue fee schedules - to identify and validate a specific trading edge or structural inefficiency.
  • Design and backtest models or signals under realistic constraints, including execution cost, latency, fee tier, and capital usage.
  • Work alongside a quantitative trader on an active cross-exchange arbitrage or basis strategy, from initial hypothesis through, where warranted, live sizing.
  • Contribute production-quality tooling to the desk's research and monitoring infrastructure.
  • Present findings to the team in writing and in person, and defend the methodology and conclusions under scrutiny.

Requirements
  • We hire principally for quantitative reasoning and technical ability; no prior experience in finance or digital assets is required or expected.
  • Currently completing, or recently completed, a bachelor's or master's degree in a highly quantitative discipline - mathematics, physics, computer science, engineering, statistics, or a related field.
  • Demonstrated excellence in programming, with proficiency in Python; working knowledge of SQL is an advantage.
  • Clear evidence of quantitative depth: competition mathematics, a strong academic record, research experience, or substantive independent projects.
  • Sound judgement under ambiguity, and the discipline to revise a position quickly when the data warrants it.
  • Excellent written and verbal communication skills, with the ability to present a technical argument clearly to a non-specialist audience.
  • Available to start immediately. This is an off-cycle intake with no fixed future start date.

Benefits

Interns work from the same desk, on the same systems, as the full-time team, with a dedicated trader or researcher as mentor for the duration of the placement, and full access to the same fifteen-plus live venues and twenty-four-hour global trading platform the desk operates on.
Job ID  FC82BCC5C5
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