This is a job posting for a Research Engineer at Flow Traders, a proprietary trading firm, seeking someone to build and scale research frameworks for systematic trading models. The role involves working closely with Quantitative Researchers, driving end-to-end ML pipelines, and shaping data-driven model development. It requires extensive experience in ML/Data Science/Research Engineering and strong Python skills.
What they want, where you stand, and the exact résumé edits to qualify.
Biggest lever: Lack of deep, specialized experience in machine learning frameworks (Ray, PyTorch) and advanced statistical/mathematical modeling, which are core to a Research Engineer role in systematic trading.
A starter prompt for Claude Code, what you'll need, and how to reach them.
Given the job description for a 'Research Engineer' at Flow Traders, outline the key technical skills and project types that an experienced candidate (8+ years in ML/Data Science/Research Engineering) should highlight on their CV and in a cover letter. Focus on Python, Ray, numpy, PyTorch, pandas, ML pipelines, modern dev practices, and cloud technologies. Structure the response as bullet points for a CV and 3-4 paragraphs for a cover letter. The goal is to maximize alignment with the stated requirements to secure an interview. Also, provide guidance on how to tailor past project experiences to demonstrate impact on 'systematic trading models' and 'data-driven model development', even if direct trading experience is limited.
Requires significant career development and specialized roles over many years, not a quick learn.
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Flow Traders | Research Engineer | Hong Kong/ London (onsite) | Full Time | Visa | Relocation Flow Traders is a leading proprietary trading firm with an entrepreneurial and innovative Tech culture at the heart of its business. We are looking for Research Engineers in our Hong Kong office. Join us build and scale the research framework behind our systematic trading models. You’ll work closely with Quantitative Researchers, drive end‑to‑end ML pipelines, and shape global standards for data‑driven model development. Research Engineers have joint responsibility for conducting research and delivering models. You’ll thrive if you have: - 8+ years in ML / Data Science / Research Engineering (Postdoc/Faculty can count towards this); - Strong Python and libraries such as Ray, numpy, PyTorch, and pandas; - Solid math/stats background; - Experience with modern dev practices & cloud technologies. If you're interested, apply here: https://lnkd.in/dWhh_m28 Or if you'd like to see other roles at Flow Traders, please check our careers website: https://flowtraders.com/careers/
Focus on building a portfolio project that involves a complete ML pipeline, from data acquisition and preprocessing using pandas/NumPy to model training with PyTorch and deployment, ideally with Ray for distributed computing. This would involve studying advanced statistics and linear algebra relevant to ML, and demonstrating practical application in a public repo (e.g., predicting a simple time series or classifying a dataset). Target 3-6 months for a solid project and foundational understanding.
Standard for data science/ML roles, aligns with general dev stack but requires deep proficiency.
Requires foundational knowledge in linear algebra, calculus, probability, and statistics — potentially formal education.
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Standard for web dev and MLOps, aligns with current operator stack like Vercel and CI/CD.
Apply directly via the LinkedIn link provided: https://lnkd.in/dWhh_m28 or the Flow Traders careers website: https://flowtraders.com/careers/
“This is a direct job application. The outreach angle is to submit a highly tailored application, demonstrating a deep understanding of quantitative research engineering in a trading context, and showcasing specific projects where you've built and scaled ML frameworks and pipelines relevant to the description.”
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