Quantitative Researcher

Placeholder; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Placeholder is seeking an exceptional quant to join the Engineering department remotely. This role involves tackling complex predictive modeling challenges in the blockchain space, significantly impacting one of the biggest upcoming projects. The ideal candidate will have at least 3 years of experience with predictive models, familiarity with techniques like linear regression and neural networks, and practical knowledge of tools such as Numpy and Pandas. Join a world-class team in an innovative environment that emphasizes collaboration and quality.

Qualifications

• At least 3 years of experience building predictive models, preferably at a HFT firm.
• Creative, self-motivated, and independent.
• Excellent knowledge of predictive modeling techniques.
• Proven ability to build something significant from scratch.
• Bonus: Crypto-native.

Responsibilities

• Work on greenfield predictive modeling problems related to blockchain performance and system/user behavior.
• Implement production-grade solutions and take end-to-end ownership of production prediction pipelines.

Skills

Predictive modeling techniques

Linear regression

Decision trees

Neural networks

Numpy

Pandas

Job description

Location

Remote

Employment Type

Full time

Location Type

Remote

Department

Engineering

The Monad Foundation is a team of dedicated ecosystem and community builders who are on a mission to massively grow the impact of decentralized tech. We believe that the Monad blockchain--the performant and parallel EVM Layer 1--will help decentralized apps eat the world.

The Role

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.

What You Will Do

• Work on greenfield predictive modeling problems related to blockchain performance and system/user behavior. Problems may be open-ended; you’ll have to devise and prototype a variety of approaches before finding the correct solution.

• Implement production‑grade solutions and take end‑to‑end ownership of production prediction pipelines.

Who You Are

• 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

Why Work with Us

• 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.