Key Responsibilities

• Analyze behavioral and transactional data to uncover insights on user adoption, retention, and engagement across digital finance products.
• Create models to evaluate on-chain activity, liquidity trends, network dynamics, and associated risk indicators.
• Design and optimize incentive and distribution mechanisms to support ecosystem sustainability and growth.
• Build quantitative frameworks for assessing platform health, capital utilization, and evolving market conditions.
• Collaborate with teams across engineering, product, and research to embed data insights into product development and strategy.
• Apply machine learning and statistical techniques to enhance predictive capabilities and inform risk management.
• Improve algorithms that govern digital asset operations, including issuance, redemption, and market balancing.
• Track key ecosystem drivers such as network growth, user activity, and capital efficiency.
• Build scalable data pipelines and develop dashboards for both on-chain and off-chain metric tracking.

Ideal Candidate

• 1–2+ years of experience in data science, quantitative research, or machine learning.
• Proficient in Python, SQL, and standard data visualization and analysis tools (e.g., Pandas, NumPy, Jupyter, Tableau).
• Experience with blockchain data and working knowledge of smart contract ecosystems and on-chain analytics.
• Familiarity with decentralized finance (DeFi), digital currencies, or tokenized systems is a strong plus.
• Solid foundation in statistics, modeling, and econometrics with the ability to apply them to real-world systems.
• Skilled in building predictive models, simulations, and data-driven decision frameworks.
• Experience with big data platforms (e.g., Spark, Snowflake) is a plus.
• Comfortable using tools such as GraphQL, Dune, Flipside, or similar analytics platforms.
• Passionate about using data to shape the future of digital economies and financial infrastructure.
• Currently pursuing or recently completed a Master’s or PhD in a quantitative or technical field from a leading academic institution.

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