The Senior Data Scientist will lead research efforts in analyzing crypto market data, focusing on data sourcing, accessibility, and usability, while applying statistical and machine learning techniques to derive insights and improve trading strategies. The role emphasizes staying current with industry advancements and benchmarking model performance.
The individual in this role will be a part of a new Data Science team, which is focused on generating extensive research across the crypto market and blockchain. The ideal candidate has experience in large-scale data processing and understands the data science workflow. This opportunity will provide the right candidate an opportunity to have a large impact on the research direction and productivity of a newly formed effort within a successful proprietary trading firm.
Responsibilities:
- Data Sourcing: Identify high-quality and relevant data to support research objectives, then create corresponding tickets for the data team.
- Data Accessibility and Usability: Develop and maintain tools and platforms for better visualization and exploration capabilities for the research team.
- Identify Patterns and Trends: Apply statistical and ML techniques to analyze historical data, detecting patterns and trends for trading strategies and research teams.
- Research and Development: Stay updated on the latest advancements in data science and the crypto industry by monitoring research, industry reports, and attending relevant events.
- Benchmarking: Regularly evaluate and improve existing models by benchmarking their performance against state-of-the-art techniques.
- Performance Metrics: Developing metrics and dashboards to track the performance of trading strategies, individual symbols, and the overall portfolio (including PnL attribution).
Requirements:
- Minimum 5 years in data science field, 2 years in leadership roles
- Master’s degree in EE, CS, Physics, Mathematics or other relevant discipline
- Background in large-scale data processing and analysis
- Skilled in Python programming
- Familiar with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experienced in modeling and forecasting, especially time series analysis (e.g., NLP)
- Experienced in developing and articulating model architecture, strongly emphasizing code quality for effective system design.
- Crypto industry knowledge is helpful but not a requirement.
- Experience in finance and trading is beneficial but not required
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