Crypto Data Scientist (Bulgaria-Remote)
Token Metrics is in need of a skilled machine learning engineer to optimize their machine learning systems, including evaluating and enhancing ML processes, performing statistical analysis, and improving predictive automation capabilities of AI software.
As a machine learning engineer, you will be required to have a strong background in data science and demonstrate expertise that contributes to the performance of predictive models.
Responsibilities:
- Collaborate with management to define and refine machine learning goals.
- Develop machine learning systems and AI for predictive automation.
- Implement ML algorithms and tools to transform data science prototypes.
- Ensure accuracy of user recommendations generated by algorithms.
- Solve complex problems using multi-layered data sets and optimize existing ML frameworks.
- Design ML algorithms for analyzing large volumes of historical data.
- Conduct stress testing, statistical analysis, and interpretation of test results under varying market conditions.
- Document machine learning processes.
- Stay updated on advancements in machine learning technology.
Requirements:
- Bachelor's degree in computer science, data science, mathematics, or related field.
- Master’s degree in computational linguistics, data science, data analytics, or similar is a plus.
- Minimum of two years' experience as a machine learning engineer.
- Proficiency in Python, Java, and R.
- Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
- Strong understanding of mathematics, statistics, and algorithms.
- Excellent analytical and problems-solving skills.
- Effective communication and collaboration abilities.
- Outstanding time management and organizational skills.
Token Metrics: Token Metrics assists crypto investors in constructing profitable portfolios through AI-driven crypto indices, rankings, and price predictions. The company caters to a diverse range of clients globally, from individual investors and traders to crypto fund managers in over 50 countries.