- Develop trading strategies which outperform Bitcoin
- Identify valuable and predictive data sources
- Build unique indicators and metrics to drive investment decisions and signals
- Skilled in investment risk-reward decision making
- At least 2 years of experience working as a trader or doing quantitative research at a well respected fund or research firm
- A mathematical back-ground either through education (degree in Maths, Statistics, Data Science, or another Science related subject) or equivalent past experience
- Track record of profitability (could be a realistic backtest, algorithmic or manual live-trading track record)
- Data modeling skills (experience in Python or other data science language)
- Expertise in finding, integrating, optimizing and analyzing new datasets
- Quantitative mindset
- Creativity in coming up with new trading ideas and approaches
- Expertise in trading Bitcoin, altcoins and/or other crypto assets in a professional fashion
- Experience in working in a research and trading oriented team
- Systematic approach and attention to detail
- Interview process: typically involves 2-3 interviews, with the second one revolving around a project and/or provision of evidence of their live trading capability
- Salary fork: not disclosed upfront but compensation will be competitive and based on prior experience and location
- Salary make up: Pay will consist of fixed salary, bonus and equity
- Starting date: as soon as possible
- 8 hour shift
- Bachelor's (preferred)
- Trader: 2 years (required)
Company
FTNM Recruits
United Kingdom
Location
Remote Position
(From Everywhere/No Office Location)
Job type
Full-Time
Python Job Details
Traders monitor markets in real time, improve our trading algorithms, and dig into data to create better models. We’re looking for candidates with a strong quantitative background who are comfortable thinking in terms of probabilities and expected value.
More details:
Requirements:
Offer:
Job Type: Full-time
Salary: From £100,000.00 per year
Schedule:
Education:
Experience:
Work Location: Remote
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