Machine Learning expert in financial markets for Neotic
Neotic (currently www.DailyStockSelect.com) has a new opening for a machine learning programmer. The new recruit will work in a small team of 3 programmers on implementing machine learning tools for financial data analysis. We already have an “in house” product – most of the coding will be on optimization of existing algos.
Neotic is a fast growing startup set to become a world leader in building AI tools for stock markets analysis. Our data cover historical stock prices, key events, corporate fundamentals and financial news.
- Position: Machine Learning expert in financial markets
- Job Description:
- Implementing new ML algos
- Communicating with stock traders
- Providing full documentation
- Reporting weekly on work progress
- Required Skills:
- Excellent English skills
- Perfect mastering of Linux, Python, Databases (we use Postgres but it could be any SQL)
- Good general understanding of ML libraries
- High baccalaureate and university grades in mathematics (no specific academic background, can be self-taught)
- Good sense of discipline and self-learning (work hours 8 am to 5 pm including 1 hour pause, no social media are allowed at the company)
- Hiring procedure:
- Starting with 3 Months probation period in order to see your creative and relational abilities. At the end of the probation period a job may be offered if outstanding practical skills are shown.
- Interested candidates can send a cover letter in English (minimum 10 lines to explain their motivation for this job and the connection between their skills and our requirements) in addition to a CV (preferably infographic) to fac@DailyStockSelect.com (CC: sez@DailyStockSelect.com).
- 8 to 16 k USD annual depending on your skills and previous experience.
- A stock options plan will be conceived in order for you to acquire more shares in the company the more performance you show (you ll become owner of a certain percentage in the company).
- Transportation fees and small pocket money will be provided during the probation period.