Python Job: Quantitative Strategist - DeFi

Job added on

Company

FTNM Recruits
United Kingdom

Location

Remote Position
(From Everywhere/No Office Location)

Job type

Full-Time

Python Job Details

London based investment firm running liquid DeFi strategies. We are a dynamic team with a background in investment management, data science and crypto.
We are looking for a Quantitative Strategist with experience in DeFi – someone who will develop quantitative strategies as part of the broader liquid DeFi portfolio. You would be working with our Portfolio Manager and Data Engineers to design, test and implement strategies. This is an opportunity to work at web3’s innovation frontier and have a direct impact on the growth of the company.
If you are insanely passionate about crypto. If you can’t imagine not playing with every new DeFi platform that pops up; if in the last year you spent more time on-chain than outside – then this opportunity is for you.

Requirements

  • Exceptional understanding of and experience with common data science toolkits
  • Excellent programming skills in Python (especially libraries like web3py and asyncio), JavaScript or other scripting languages.
  • Experience with financial markets, especially pertaining to market microstructure, algorithmic trading, signal development, and backtesting mid to high frequency strategies
  • Expertise in applied statistics skills, such as distributions, statistical testing, regressions
  • Excellent understanding of and some experience with machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests
  • Great communication skills and data-oriented personality
  • Deep understanding of Uniswap v2 and v3 contract structure and other DEXs. We will test.
  • Experience in Solidity is not a must but will be considered as a plus

Job Type: Full-time

Salary: From £100,000.00 per year

Schedule:

  • 8 hour shift

Experience:

  • Python: 3 years (required)
  • Financial Markets: 3 years (required)
  • Web3: 3 years (required)

Work Location: Remote