Algo Trading Quant
Who Are We? Decentralized Masters is at the forefront of DeFi education globally. In just two years, we have grown from a pioneering pair of co-founders to over 140 dedicated professionals. Today, we are recognized as one of the fastest-growing enterprises in the sector, with industry insiders predicting our evolution into a unicorn company by 2030. Operating on a bootstrapped model, we are on track to achieve an impressive $50 million in revenue this year alone. Our Impact While our growth has been remarkable, we take even greater pride in the success of our clients. To date, we have empowered over 4,000 investors to break into the DeFi world. At Decentralized Masters, we don't just offer education; we cultivate a powerhouse of knowledge combined with an engaging community, innovative technology, and a team of leading DeFi and blockchain experts. Our commitment is to deliver unparalleled resources designed for long-term success in the world of DeFi and Web3, ensuring our members not only safeguard but also enhance their financial future.
Our Vision
Our goal is to create the largest and most influential DeFi ecosystem the world has ever seen, starting with becoming the gold standard in DeFi education. This vision is ambitious, transformative, and poised to change the landscape of digital finance. Are You Ready? This is more than just a job; it's an opportunity to shape the future of Web3 technology and algorithmic trading. You won't be building strategies in a vacuum - your work will directly power a product used by hundreds of paying members. Are you ready to be part of our vision to redefine what's possible in DeFi and beyond? Apply below, and let's explore this journey together. Check us out here: Decentralized Masters What Will You Be Doing? The Algo Trading Quant will be a critical hire responsible for designing, building, and deploying automated quantitative trading strategies on decentralized perpetual exchanges. You will work alongside our existing quant as a peer - independently creating strategies while rigorously reviewing and stress-testing each other's work before anything goes to production. This dual-quant model is central to our approach: two minds, two independent strategy pipelines, mutual accountability, and dramatically reduced single-point-of-failure risk. Your strategies are the product. They are what our members pay for. This is not research for the sake of research - you will own short-term and long-term P&L outcomes, and your work will have immediate, measurable commercial impact.
Key Responsibilities
Strategy Design & Research
- Design and implement predictive quantitative trading models, including both market-making and directional strategies, for automated execution on decentralized perpetual exchanges such as Hyperliquid.
- Apply statistical modeling and research methodology - including regression analysis, time-series forecasting, and machine learning - to identify and validate trading signals across varying time horizons.
- Lead research efforts to discover new alpha sources, optimize strategy parameters through rigorous backtesting, and expand the number of available strategies to support growing user capacity.
- Perform experiment design, dataset generation, feature engineering, and model building on financial datasets, following the full research-to-production pipeline.
- Run simulations and estimate market impact of quantitative models, accounting for realistic assumptions around slippage, fees, funding rates, and liquidity constraints.
- Proactively identify trading opportunities and risks by analyzing historical market data across multiple markets and instruments.
Development & Production
- Write clean, well-documented, production-grade code with proper version control (Git), testing, and deployment practices.
- Own the full development cycle: from initial research and prototyping through deployment into production and ongoing maintenance of live trading systems.
- Build and maintain robust backtesting infrastructure that produces unbiased estimates versus live realization, reflecting the limitations of available infrastructure.
- Monitor live strategy performance in real time, diagnose issues, and iterate on models based on production data and changing market conditions.
- Analyze performance metrics and other quantitative measures to inform decisions about trading system design and improvements.
- Implement and maintain trading models, ensuring seamless transition from research to live trading with automated deployment pipelines.
Collaboration & Risk Reduction
- Collaborate with the existing quant as a peer reviewer - independently creating strategies while validating, challenging, and stress-testing each other's work before production deployment.
- Participate in strategy review sessions where both quants present their models, assumptions, and results for mutual critique and refinement.
- Contribute to internal documentation, research frameworks, and knowledge-
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