Quantitative Researcher

Tardis Group; Hong Kong; On-site; HKD 700,000 - 1,100,000; Full time

Job summary

Tardis Group seeks a quantitatively minded researcher to help discover, test, and implement trading signals. You will work closely with senior researchers and portfolio managers in a hands-on role to learn the mechanics of systematic investing from the ground up.

The position emphasizes strong analytical skills, data-driven problem solving, and a passion for financial markets as you develop and transition research into live strategies.

Qualifications

• Master’s degree or PhD in a quantitative field (e.g., Math, Stats, CS, Physics, Finance).
• Proficiency in Python data analysis with Pandas and NumPy.

Responsibilities

• Idea generation: research alternative data sources and alpha factors.
• Backtesting and analysis: design, test, and evaluate trading strategies using historical data.
• Data wrangling: clean and organize large research datasets.
• Collaborate with engineering teams to move research into live production.

Skills

Analytical mindset

Curiosity & drive

Education

Master’s or PhD in a quantitative field

Tools

Python

Pandas

NumPy

Job description

In this role, you will work closely with senior researchers and portfolio managers to discover, test, and implement quantitative trading signals. This is a hands‑on position ideal for someone with a strong analytical foundation who is eager to learn the mechanics of systematic investing from the ground up.

Key Responsibilities

• Idea Generation: Brainstorm and research alternative data sources and quantitative alpha factors.
• Backtesting & Analysis: Design, test, and evaluate trading strategies using historical market data.
• Data Wrangling: Clean, process, and organize large datasets to ensure high research integrity.
• Collaboration: Partner with engineering teams to help transition validated research strategies into live production environments.

Candidate Requirements

• Education: Master’s degree or Ph.D. in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Physics, Finance, or Engineering).
• Programming Skills: Proficiency in Python (Pandas, NumPy) for data analysis and research.
• Analytical Mindset: Strong foundation in probability, statistics, and data-driven problem-solving.
• Curiosity & Drive: A genuine passion for financial markets and a strong desire to learn systematic trading strategies.