Quant Researcher｜Strategy Research & Development

About Us

Jade Capitech is an Asia-based quantitative hedge fund company, with Hong Kong as its core operating base and Taiwan as its R&D center. We serve high-net-worth clients, business owners, and corporate capital across Asia.

Our vision extends beyond strong returns – helping investors build long-term wealth and reach their financial goals through smart innovation.

The Role

We are looking for a Quant Researcher with strong independent research and strategy development capabilities.

This role requires the ability to break down investment hypotheses from 0 to 1, build strategy prototypes, conduct backtesting and validation, analyze risk and failure conditions, and turn research outcomes into strategy modules that can be adopted by fund products.

You will work closely with the Quant Lead on fund product design, strategy composition, risk control, and research direction. At the same time, you must be able to work independently, drive research tasks forward, and make sound research judgments.

We expect you to be more than someone who can write code or discuss investment views. You should be able to integrate market insight, financial engineering, data analysis, AI tools, and a rigorous validation process to produce strategy research that is truly discussable, testable, improvable, and productizable.

Responsibilities

1. Strategy Research & Investment Hypothesis Design

• Break down market phenomena, investment logic, and strategy hypotheses independently.
• Research strategies across U.S. equities, ETFs, futures, multi-asset portfolios, technology stocks, factors, momentum, volatility, risk control, and asset allocation.
• Identify strategy ideas from market structure, behavioral finance, capital flows, macro conditions, and trading logic, and translate ambiguous investment concepts into testable strategy rules and research plans.
• Support fund product design by defining strategy modules, risk positioning, and research priorities.

2. Python Strategy Research & Development

• Build strategies and backtesting frameworks from 0 to 1 using Python.
• Process financial time series data, signals, portfolio construction, transaction costs, and risk metrics.
• Convert strategy ideas into testable notebooks, scripts, or research modules.
• Help build a more efficient and repeatable internal strategy research process, and turn research outcomes into strategy modules and research assets that can be continuously iterated on.

3. Backtesting, Performance Analysis & Risk Research

• Design and execute backtests, parameter sweeps, robustness tests, and regime analysis.
• Analyze CAGR, MDD, Sharpe, Sortino, turnover, beta, correlation, drawdown, recovery, and related metrics.
• Evaluate strategy stability, risk sources, failure conditions, and improvement directions across market regimes.
• Identify backtesting bias, data issues, overfitting, trading friction, and model blind spots.

4. AI-Native Research & Financial Engineering Integration

• Use AI tools deeply for research, coding, data analysis, literature review, code review, and research memos.
• Integrate AI tools with financial engineering, investment strategy, statistical validation, and risk management.
• Maintain independent thinking and validation discipline rather than relying blindly on AI outputs.
• Help build AI-native quantitative research workflows for faster strategy development, testing, validation, and documentation.

Growth Path

The short-term goal is to become a core strategy researcher within Jade Capitech’s quantitative research team, independently taking on strategy research tasks and delivering investment strategies ready for real-world testing.

The long-term path is toward becoming a:

Quant Trader

with capital management ability, trading judgment, risk awareness, and strategy decision-making capability.

In this role, you will learn:

• Quantitative Strategy R&D: investment hypotheses, signal design, backtesting, and strategy iteration.
• U.S. Equity & Global Markets: U.S. equities, ETFs, technology stocks, sector rotation, multi-asset allocation, and market regimes.
• Financial Engineering & Asset Allocation: portfolio construction, risk budgeting, volatility targeting, drawdown control, hedging, and multi-asset allocation.
• Practical Strategy Research: how to judge market logic, stability, tradability, and investability.
• Risk Control & Performance Evaluation: return sources, failure conditions, backtesting bias, transaction costs, and risk-adjusted performance.
• AI-Native Research Methods: using AI to accelerate research, coding, literature review, strategy testing, and documentation.
• Fund Product Thinking: how research outputs become fund products that can manage real capital.
• High-Intensity Research Collaboration: advancing strategy R&D with speed, rigor, and discipline.

Requirements

Required

• Master’s degree or above, preferably in financial engineering, finance, statistics, mathematics, computer science, or another highly quantitative field.
• 3+ years of experience in quantitative research, investment research, data science, financial engineering, trading strategies, asset management, fintech, or related R&D roles; 5+ years or proven ability to complete strategy research projects independently is preferred.
• Strong Python skills, with the ability to independently complete data processing, strategy prototyping, backtesting, performance analysis, and research reports.
• Real investment, trading, asset allocation, or strategy research experience.
• Strong familiarity with the U.S. equity market, including major indices, ETFs, technology stocks, sector rotation, volatility behavior, and basic market structure.
• Ability to break down strategy hypotheses from 0 to 1, write strategy prototypes, validate results, and organize research conclusions.
• Familiarity with financial time series, performance metrics, risk control, backtesting validation, and basic statistics.
• Advanced use of AI tools for research and development, with the ability to integrate AI tools with financial engineering knowledge.
• Independent thinking, with the ability to question assumptions, model outputs, backtesting results, and AI-generated outputs.
• Ability to work effectively in a high-intensity, fast-paced, and uncertain research environment.

Preferred

• Personal trading records, strategy research work, GitHub projects, research notebooks, paper replications, or investment research reports.
• Understanding of equities, ETFs, futures, options, crypto, or multi-asset investment strategies.
• Experience with momentum, trend following, factor investing, risk parity, volatility targeting, portfolio optimization, machine learning, time series modeling, or regime analysis.
• Familiarity with crypto markets, on-chain assets, crypto ETFs, exchange microstructure, or Web3 capital behavior.

Work Setup

• Location: First six months primarily remote for internal work, with availability required for meetings, research discussions, and team activities in Taipei. Taipei will become the main work location afterward.
• Type: Full-time
• Compensation: Annual salary from NT$1,200,000+, negotiable based on capability, experience, and research portfolio.
• Bonus: OKR-based, tied to strategy research output, backtesting quality, research documentation, strategy iteration contribution, and collaboration performance.

Apply

Send your resume, brief introduction: info@jadecapitech.com

Email subject: Quant Researcher｜Your Name