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:
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Data Sourcing: Identify high-quality and relevant data to support research objectives, then create corresponding tickets for the data team.
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Data Accessibility and Usability: Develop and maintain tools and platforms for better visualization and exploration capabilities for the research team.
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Identify Patterns and Trends: Apply statistical and ML techniques to analyze historical data, detecting patterns and trends for trading strategies and research teams.
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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.
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Benchmarking: Regularly evaluate and improve existing models by benchmarking their performance against state-of-the-art techniques.
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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
