The board
- Pay
- $50 per hour
- Where
- London, NYC
- Posted
- Sep 8
Institutional Fabric for the Digital Asset Market
Founded in 2018, Talos provides institutional-grade trading technology for the global digital asset market, powering many of the major players in the crypto ecosystem. Our mission is clear: to advance the mass adoption of digital assets by seamlessly connecting institutions to the digital asset ecosystem. We are committed to building the most innovative and trusted platform in the world, supporting the entire trading lifecycle.
At Talos, you’ll find an environment that champions kindness and respect, values diverse perspectives, and upholds inclusivity at every turn. We believe every member of our team brings invaluable insights and abilities that drive Talos forward.
What you'd do
- Assist in analyzing trading data, proprietary intraday signals, to produce quantitative execution alphas
- Help create bespoke analytics visualizations using Talos data to illustrate trading patterns and execution insights
- Learn to use internal tools and systems for data analysis
- Work with Talos quants upon quantitative strategies that utilize execution alphas to drive trading decision making
- Help gather and organize data related to trading algorithm performance
- Learn about market microstructure and best execution practices
- Assist in preparing quantitative content for client meetings, presentations and academic research reporting
- Work with the Quant strategies to backtest real-world trading features for the pleasure of top leading crypto firms in the space
What they want
- Graduating class of 2029 pursuing a Masters or Doctorate degree in Computer Science or related field
- Programming Skills: Advanced proficiency in Python, with hands-on experience in data science libraries (especially pandas) and a strong understanding of dataframe architecture for data manipulation, transformation, and analysis.
- Familiarity with Python-based data visualization tools is a plus.
- Database and Query Languages: Experience with SQL, including constructing and optimizing complex queries for large datasets; experience with BigQuery or other cloud-based querying platforms is a strong advantage.
- Computational Finance: Exposure to computational finance concepts, with familiarity in using quantitative methods and tools for finance-related applications.
- Statistics and Data Analysis: Strong statistical knowledge, including probability distributions, hypothesis testing, and data sampling methods. Ability to apply statistical analysis techniques to analyze financial data.
- Mathematics and Machine Learning: Solid foundation in mathematical principles, including linear algebra and calculus, with a focus on regression analysis.
- Exposure to machine learning and deep learning algorithms and methods in the presence of sparse data, including common imputation approaches. .
- Portfolio Optimization: Knowledge of portfolio optimization methodologies, specifically the Markowitz risk-return models is a plus.
- Local to New York HQ
- Market Impact Modeling: Understanding Market Impact in Crypto Trading: The Talos Model for Estimating Execution Costs | Youtube
- Execution Alphas: Youtube
What you get
- A lunch credit of $25 USD towards lunches for days in-office
- Evening socials with the entire office and fellow interns
- Other in-office perks: Catered lunches on Tuesdays, snacks, and drinks