Quant Analyst

Quant Analyst – Quantamental Research

Dark Ice Research is a boutique quant research firm based in Hong Kong, focusing on US and APAC equities. We are hiring a Quant Analyst to join our quantamental research effort — the work of turning genuine fundamental insight into systematic, machine-driven signals. You'll work closely with senior practitioners who'll mentor you, and take real ownership of your work as you grow into the role.

 

Quantamental research — this is the core of how Dark Ice generates edge: deploying fundamental understanding systematically, at a scale and consistency discretionary analysis can't reach.

• Help translate fundamental theses into systematic, testable factors — turning the kind of judgment a seasoned equity analyst makes into signals that can be ranked, backtested, and traded across a broad universe
• Financial-statement analysis at scale: quality of earnings, accruals, cash conversion, balance-sheet strength, capital allocation — applied cross-sectionally rather than name-by-name
• Contribute to fundamental factor libraries (value, quality, growth, profitability) grounded in real accounting understanding
• Support development of sector- and market-specific fundamental models across US and APAC equities, accounting for local accounting standards and market structure
• Research corporate-event and catalyst signals — placements, buybacks, ownership changes, governance-driven re-ratings — where a fundamental read drives the systematic response

 

Machine learning

• Build, train, and validate ML and deep-learning models that turn fundamental, market, and alternative data into predictive signals
• Rigorous feature engineering and out-of-sample discipline in a low-signal, non-stationary domain
• Apply modern techniques with growing judgment about when simpler methods win
• Extract signals from unstructured text — news, filings, transcripts — using LLM and NLP techniques

 

Foundation

• Analysis of large financial and market datasets in Python and SQL, with rigorous point-in-time correctness and data quality
• Sourcing, curating, and analysing alternative datasets to uncover new edge
• Building bias-aware backtesting tools for multi-factor and cross-sectional models
• Automating and optimising research and data workflows

 

What we're looking for

• Hands-on experience building ML / deep-learning models on real prediction problems — through study, projects, competitions, internships, or early professional work you can walk us through and explain the choices behind
• Solid grounding in financial-statement analysis and fundamental valuation, or clear aptitude and appetite to build it fast
• Fluent in Python and the modern ML stack; disciplined about validation and wary of overfitting
• Strong quantitative degree (or equivalent self-taught evidence) and genuine curiosity about markets
• Exposure to a quant, systematic, or quantamental environment is a plus, not a requirement — we invest in the right person

 

What you get. Direct work on the models that drive the firm's live strategies, close mentorship from senior practitioners, and real ownership as you grow. Market base plus discretionary annual bonus and long-term incentive.