United States onlyInjective Labs is trailblazing a new dawn for Web3 enabled finance. We are the core contributors to Injective, one of the fastest growing blockchains in the industry. Injective provides an interoperable smart contracts platform that is optimized for building decentralized finance applications. Interoperability is at the core of Injective, which is natively integrated with chains such as Ethereum, Cosmos and Solana. Developers can rapidly launch premier financial applications suited for mass adoption using Injective’s infrastructure and specialized DeFi primitives such as the world’s first fully on-chain order book. Our team has decades of experience spearheading the largest financial institutions and tech organizations. Injective is incubated by Binance and is backed by leading firms such as Jump Crypto, Pantera and Mark Cuban.
About the role
As a Quantitative Research Intern at Injective Labs, you will work closely with our research team to develop and implement statistical models and machine learning algorithms. This internship offers a unique opportunity to gain hands-on experience in quantitative research, statistical modeling, and data analysis within the dynamic field of DeFi.
Key Responsibilities:
- Assist in developing and implementing statistical models, machine learning algorithms, and other quantitative methodologies.
- Conduct research and statistical analysis to identify market opportunities and inform protocol decisions.
- Support research efforts to improve signals across a wide range of DeFi products and technologies.
- Work collaboratively with a cross-functional team of developers, engineers, product managers and leadership to evolve and execute the product roadmap in a time efficient manner.
- Run simulations and estimate market impact of quantitative models, for both liquid and illiquid assets.
Qualifications:
- Currently pursuing or recently completed a Master’s or Ph.D. degree in Math, Statistics, Physics, Computer Science, or a related field.
- Quantitative research/analysis skills with coursework or project experience.
- Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems.
- Ability to write and implement statistical ideas in Python, R, C++, or related program.
- Strong communication skills and ability to work effectively in a team environment.
