Data scientist

Agio is a VC-backed startup transforming how digital asset traders manage counterparty risk. We believe the industry needs to move past Twitter and Telegram as its main sources of risk data.  Our team of PhD researchers have developed a model with an industry-leading record of predicting defaults. We’re now working with the top institutions in digital assets to push the industry forward.   

We’re excited to bring on a data scientist who can apply machine learning and statistical models to rate counterparty risk. At Agio, you’ll be joining a pioneering and results-oriented team. We’re seasoned operators who have helped to launch unicorns and led companies to multi-million dollar exits. Our team hails from world-class institutions (Morgan Stanley, HSBC, the Federal Reserve) and universities (Harvard, Oxford, Cambridge). This is your opportunity to build alongside the most driven, curious, and accomplished professionals in the industry.

*Responsibilities *

• Cleaning and modeling data sets such as: web traffic and social media feeds, on-chain wallet transaction flows and ad-hoc primary data sources
• Develop forecasts with various methods including:
• Regression models (linear, logistic, multivariate)
• Time-series analysis (ARIMAX, Cox Hazard)
• Natural language processing (RoBERTa)
• Consulting with internal and client stakeholders to understand their needs
• Authoring presentations for clients, regulators and investors

Requirements

• Degree in Data Science, Mathematics, Statistics, Physics, Engineering or related field
• Programming experience with R and/or Python, including common data science libraries such as: dplyr, ggplot2, data.table, shiny (in R), scikit-learn, statsmodels and pandas (in Python)
• Experience working with cloud computing platforms like Azure or AWS
• Ability to run scripts and interact with MongoDB
• Ability work with APIs or scrape data from online sources
• Minimum B2 level proficiency in English

Nice-to-have

• Prior work experience with financial or data products
• Proven interest in digital assets