Quantitative Researcher (algorithmic trading platform)

At Alpha9 we aim to define the global standard in quantitative, systematic digital asset management. Using our proprietary alpha engine, we deliver cryptocurrency investment products to some of the world’s leading financial institutions. Join us as a Quantitative Researcher and help shape something exceptional.

Role Overview

As a Quantitative Researcher at Alpha9, you will be the architect behind our next generation of systematic trading strategies. In this pure research role, you will apply advanced statistical methods to discover alpha, driving the full lifecycle of algorithm development from hypothesis to deployment. You will leverage our repository of proprietary data and institutional-grade modeling infrastructure to stress-test signals across diverse volatility cycles. This is an opportunity to solve complex market inefficiencies alongside some of the sharpest minds in crypto trading. 

In this role, you will get to:

• Research & Model Development: Design, develop, and optimize quantitative models for cryptocurrency markets. Translate financial and market hypotheses into data-driven models with documented assumptions and results.
• Alpha Generation: Identify and research trading opportunities through systematic approaches and algorithmic strategies. 
• Backtesting & Validation: Conduct rigorous backtesting of trading strategies to validate model performance and robustness
• Crypto Market Analysis: Explore and research a wide range of crypto instruments, including options and derivatives
• Collaboration: Partner with the Software Engineering team to refine execution logic and optimize the data pipelines that power your models in production.

You'll be successful if you have:

• Education: Degree(s) in a STEM discipline (Math, Stats, CS, Engineering, or similar).
• Drive: A strong competitive drive, a demonstrated passion for trading (in a personal or professional setting), and a genuine curiosity about the crypto markets.
• Coding: Strong Python skills, specifically in data analysis and scientific computing (e.g., Pandas, NumPy).
• Analysis: Experience applying statistical models to data sets.
• Language: Excellent written and verbal English skills.

It’s a plus if you have:

• Hands-on experience with backtesting frameworks and quantitative evaluation of trading strategies
• Solid understanding of financial markets and instruments
• A proven track record of developing profitable quantitative trading models