DV Trading is hiring a Quantitative Researcher in DV Equities — London. The overview below is synthesized from the employer posting on job-boards.greenhouse.io: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
About Us
Company context from the listing:
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Founded 20 years ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people operating throughout North America, Europe and Asia. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users.
Overview
Company context from the listing:
The listing frames the Quantitative Researcher at DV Trading as a hands-on product role. This role is ideal for someone early in their career who has hands-on experience working with limit orderbook data and a genuine curiosity about how markets function at the tick level. You'll work closely with senior researchers and traders to develop, test, and refine predictive signals and models that inform trading decisions.
Responsibilities
Day-to-day scope for the Quantitative Researcher as described in the posting:
- Analyze high-frequency limit orderbook data to identify patterns, inefficiencies, and predictive signals
- Build and backtest quantitative models using historical tick and orderbook data
- Collaborate with senior researchers and traders to translate research findings into production-ready strategies
- Develop and maintain data pipelines for processing large-scale, high-frequency market data
- Apply statistical and machine learning techniques, particularly tree-based methods, to improve signal quality
- Continuously monitor and iterate on live signals and models based on performance
Requirements
Experience and skills the team lists as required:
- 1–3 years of professional or research experience working directly with orderbook / limit order book (LOB) data
- Technical degree/background in a quantitative field (Math, Statistics, CS, Physics, Engineering, Financial Engineering)
- Strong proficiency in Python, including standard data science libraries (pandas, NumPy, etc.)
- Genuine interest in financial markets and market microstructure — you follow markets, not just models
- Solid foundation in statistics and quantitative analysis
- Strong problem-solving skills and intellectual curiosity
- Ability to communicate technical findings clearly to non-technical stakeholders
DV is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with DV should submit resumes in response to DV’s posted positions.
Build a standout application
For the Quantitative Researcher at DV Trading, reviewers look for concise evidence over buzzwords. Mirror the language of the posting sparingly, quantify support or delivery outcomes, and show how you handled ambiguity, time-zone collaboration and user empathy. Keep your resume to impact, keep your cover note to one page, and link to artifacts — tickets resolved, docs shipped, dashboards owned — that prove you can operate in a fast-moving Web3 team. Prepare to discuss a time you turned a confusing user report into a clear fix and how you measure quality in support and operations.
Web3 hiring values reliability: on-time follow-through, clear writing, and a track record of improving runbooks and tooling. Treat the application as a work sample. For interviews, be ready to walk through how you prioritize across time zones, handle a difficult user, and decide when to escalate versus resolve directly. Show how you document decisions so the next teammate benefits.
In a distributed Web3 org, trust builds through written clarity. Use the cover note to demonstrate it.