Quantitative Researcher

We are looking for an exceptional quant to work on data science and machine learning problems in the blockchain space. The work will be challenging, as it will involve predictive modeling for a variety of topics like transaction dependencies, user behavior, network behavior, etc. We’re looking for someone who has excelled in other environments where predictive analytics had a direct impact on the bottom line, such as high-frequency trading or traditional tech. Your work will directly impact the performance and economics of one of the biggest upcoming blockchain projects in the space.

At least 3 years of experience building predictive models, preferably at a HFT firm

You’re creative, self-motivated and independent

You have excellent knowledge of predictive modeling techniques including linear regression, decision trees, and neural nets

You know numpy and pandas like the back of your hand

You’ve built something significant from scratch

Bonus: You are crypto-native

Challenging problems. You’ll tackle deeply complex and technically demanding problems, with autonomy and impact.

Endless Opportunity for Impact. The Ethereum Virtual Machine (EVM) standard is ubiquitous, but existing EVM-compatible chains are slow and bandwidth-constrained. Monad’s core innovations offer developers and founders the best of both worlds (portability and performance) and are a game-changer to power global on-chain finance.

The right team. You’ll be part of a world class team, who are exceptional and highly-motivated.

Culture . We’re a lean team working together to achieve very ambitious goals. We are united in our culture of collaboration, low ego, and high-quality output.

Strong Ecosystem . The broader Monad ecosystem has attracted support from leading investors, builders and long-term contributors.