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:

Duration: Initial three-month contract, with the potential to become permanent.

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.