
Quantitative Researcher
1 week ago
Selini Capital - Job Description
Role: Quantitative Researcher
Location: London, Singapore or NYC
Working Pattern: Office-Based
About Selini:
Selini is a global trading firm focused on systematic trading and venture investing, all within the digital assets space.
The Role:
Selini Capital is seeking a highly analytical and technically gifted Quantitative Researcher to join our high-frequency trading team. In this role, you'll focus on refining features, designing better models, and advancing core research pipelines. You'll collaborate closely with other researchers and engineers to push the boundaries of what's possible in highly competitive electronic markets.
The ideal candidate is a curious, rigorous thinker with a strong technical foundation and a bias toward empirical validation. You enjoy working with data, building systems to understand it, and using that understanding to drive performance.
Responsibilities:
As a Quantitative Researcher, you will:
- Design, test, and refine features and model architectures to improve prediction and execution performance
- Develop and improve research pipelines and tools for large-scale strategy simulation and optimization on a cutting-edge compute cluster
- Conduct deep-dive analyses of market data, live strategy behavior, and model outputs to guide iterative improvements
- Stay up-to-date on advances in quantitative methods, ML, and optimization — applying new insights to real-world challenges
Why This Role Is Unique:
- Research First - This role is research-heavy — you'll be focused on signal improvement, model fidelity, and hypothesis generation, not plumbing infrastructure or devops.
- Breadth and Depth - You'll work at every level of the alpha stack: from feature design and statistical modeling to optimizer tuning
- Direct Feedback Loop - We deploy and iterate quickly. Your work will feed directly into live strategies and have measurable real-world impact
- World-Class Environment - Join a high-talent, low-ego team with experience across elite trading firms, olympiads, and academic research
Core Qualifications:
- 1–5 years of experience in quantitative research, applied ML, or statistics
- Fluency in Python and/or C , with the ability to translate research concepts into performant, production-ready implementations
- Strong knowledge of algorithms, linear algebra, statistics, and optimization techniques
- Ability to uncover meaningful structure in noisy, high-frequency market data — from alpha signal extraction to modeling order book behavior
- Can take research ideas from concept to experimental evaluation with minimal supervision
Signals of Excellence:
- Track record of PNL generation using model-driven strategies
- Outstanding academic record in a quantitative field
- Strong performance in competitive programming or quantitative olympiads
Company Culture & Team Fit:
We're a close-knit team that values:
- High ownership and initiative
- Curiosity, intellectual honesty, and rapid learning
- Clear, direct communication
- Working together toward shared goals — no ego, no politics
We hire people who love building, solving, and improving — and who want to learn from and contribute to a team of exceptional peers.
Compensation & Benefits:
- Very competitive compensation salary with and strong upside based on contribution and performance comprehensive benefits package.
- Free Deliveroo lunch ordered to the office every day in the office.
- Opportunity to work with cutting-edge technology in a challenging and rewarding environment.
- Chance to make a significant impact on the firm's trading performance.
- Collaborative and intellectually stimulating work environment.
- Competitive Annual Leave and Pension Contribution
- High-spec office with state of the art equipment and standing desks
- Monthly team breakfast
- Regular London onsites with focus groups in different business coinciding with team dinners and evening events
- Annual Company Offsite in luxury location
- Inter-office travel encouraged to promote the Selini culture and cross-business unit collaboration
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