Entry Level Data Scientist
DeFiner is a permissionless and configurable decentralized lending protocol with protected privacy. It allows users to lend, borrow, and stake any token. The protocol features a Smart Contract Factory that enables anyone to launch their own lending market on Ethereum and other EVM-compatible blockchains.
About DeFiner
DeFiner is a decentralized finance (DeFi) protocol that offers a configurable lending market with a lock-up function, known as the HODLer market. It features a Smart Contract Factory that allows anyone to create their own lending market on demand in a permissionless manner. Users can customize various aspects of their market, such as supported assets, maturity dates, and oracles. The protocol is built as a set of smart contracts on Ethereum and other EVM-compatible blockchains, enabling direct interaction for users and applications. Security is a priority, with the protocol having undergone multiple audits. DeFiner offers privacy through encrypted balance transfers with zero-knowledge proof traceability protection. Users can deposit crypto assets to earn interest, borrow against their deposits, create their own lending pools, and stake tokens to lock liquidity.
Skills
About the Role
You will work with engineering, marketing and analytics to answer product questions and drive growth. You will design and build machine learning models, analyze large datasets using structured approaches, and translate findings into clear presentations for technical and non-technical audiences. You will document and publish research and collaborate with data engineers and analysts to operationalize solutions.
Requirements
- Proficiency in SQL
- Proficiency in Python
- Experience with Jupyter Notebook
- Familiarity with R (optional)
- Strong background in mathematics and algorithms
- Ability to work in a startup environment
- Strong stakeholder management and influencing skills
- Strong organizational skills and attention to detail
Responsibilities
- Collaborate with engineering and marketing to identify and answer product questions
- Develop machine learning solutions for business problems
- Analyze large datasets to uncover insights using structured approaches
- Incorporate expertise from data analysts, data engineers, and stakeholders into data science solutions
- Present and defend results to technical and non-technical leadership audiences
- Publish and present technical research internally and externally
