Quantitative Researcher

Monad Labs; United States; Remote; USD 120,000 - 250,000; Full time

Job summary

Monad Labs is seeking a Quantitative Researcher specializing in predictive modeling for blockchain applications. You will design, validate, and deploy models that improve decentralized technology and user behavior.

You will own the full production prediction pipeline, from feature engineering to model serving, monitoring, and iteration, in a fast-evolving team that values autonomy and collaboration. The role demands a rigorous data science background and an ability to translate complex problems

Qualifications

• Strong background in predictive modeling and data science.
• Experience with end-to-end ML production pipelines.
• Familiarity with blockchain concepts is a plus.

Responsibilities

• Develop and validate predictive models for blockchain performance and user behavior.
• Own the production prediction pipeline from feature engineering to model serving and monitoring.

Skills

Predictive Modeling

Blockchain

Data Science

Production Deployment

Job description

Monad Labs is looking for a Quantitative Researcher focused on predictive modeling in the blockchain domain. This role involves building and deploying models to enhance decentralized technology. Candidates with a strong background in predictive modeling and data science should apply.

At Monad Labs, the Quantitative Researcher will tackle greenfield predictive modeling challenges that directly influence blockchain performance and user behavior. The role emphasizes ownership over the entire production prediction pipeline, ensuring that models are not only developed but also effectively implemented in a production environment.

The team values autonomy and collaboration, working towards impactful solutions in a rapidly evolving space. Candidates will engage with complex problems and contribute to a project aimed at revolutionizing decentralized applications, making it essential for them to have a deep understanding of predictive modeling techniques.