- Cross-sectional and time-series signal research
- 5+ years of relevant experience
- Take ideas from concept through to implementation
About Our Client
Starbridge Investment Management is a Hong Kong-based investment firm built around a quantamental approach — a hybrid model where quantitative research and human judgment are equally valued and continuously integrated. They are not a purely systematic fund, nor are they purely discretionary. Their core investment process combines rigorous factor research, signal generation, and portfolio construction with fundamental insight and real-world context.
It focuses on US equities and aims to deliver consistent, institutional-quality returns to our investors — including family offices, fund-of-funds, and institutional allocators.
The Role
Looking to hire one to two people on the investment side to advance our research framework. The profiles we are open to span a spectrum:
- Senior Quant Researcher (PhD preferred, focused on macro research, alpha signal development, and portfolio construction)
- Quant Analyst All-Rounder (works across both quantitative and fundamental sides, with strong execution skills)
- Fundamental Analyst with Quantitative Skills (deep company research, industry knowledge, with programming skills and comfort working with models)
If you are strong on any part of this spectrum — including if you are exceptionally strong in one dimension but lighter in another — we encourage you to apply. We will assess how you fit into the overall team structure.
Key Responsibilities
- Quant research & model-building: Factor ideation, construction, and refinement. Cross-sectional and time-series signal research. Improving existing models — better data handling, cleaner methodology, stronger statistical validation, more rigorous backtesting.
- Programming & execution: Write production-quality Python code for backtesting, signal generation, and portfolio construction. Take ideas from concept through to implementation.
- Fundamental awareness: Follow markets, read news, understand the business drivers behind the signals. Calibrate quantitative output against real-world context.
Qualifications
Required:
- Strong academic foundation: either (a) high-calibre undergraduate with STEM + business combination, or (b) PhD in a quantitative discipline (mathematics, statistics, computer science, physics, finance, economics, or related)
- Strong Python skills
- Experience in quantitative research — factor research, signal generation, backtesting, or portfolio construction
- Genuine interest in US equities and markets
Preferred:
- 5+ years of relevant experienceExperience in a quantamental environment or multi-strategy platforms
- RO eligibility
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