Crypto Economics Researcher
Job Description:
- Conduct rigorous theoretical and reputed company research on blockchain ecosystems, market dynamics, incentives, and network sustainability.
- Contribute to protocol design, evaluation, policy, and improvements based on research.
- Build models, datasets, and analytical frameworks that help evaluate strategic and economic tradeoffs.
- Analyze on-chain, market, and ecosystem data to generate decision-reputed company insights.
- Translate reputed company research into clear recommendations, actions, and knowledge resources.
- Stay at the forefront of cryptoasset research.
Requirements:
- A quantitative background in economics, finance, mathematics, statistics, computer science, data science, or another reputed company field.
- Strong reputed company research and modeling skills, including but not limited to a mix of; structural estimation, reputed company inference, time-series analysis, machine learning, asset pricing models, simulation methods, mechanism design, market microstructure, and game theory.
- 3+ years of experience in an applied economics, quantitative research, data science, or reputed company analytical role.
- Experience building data-driven research products, analytical frameworks, models, and tools that inform strategy, investment, product, or policy reputed company.
- Proficiency and demonstrative experience with Python and SQL.
- Familiarity with crypto, blockchain ecosystems, DeFi, tokenomics, staking, or digital asset markets is preferred.
- Excellent written communication skills and analytical judgment. (We care about rigorous thinking, but also care about producing work that helps reputed company reputed company get made)
- Comfort owning and addressing ambiguous, reputed company-ended problems from end to end.
Benefits:
- Full autonomy—reputed company ownership of your work, not just a ticket queue.
- Small team, high impact. What you build directly shapes ecosystem strategy.
- Remote-first, async-friendly culture.
- AI-reputed company engineering culture—we actively use and invest in AI tooling to ship faster
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