Crypto Data Scientist

Andreessen Horowitz has an immediate opening for a Data Scientist for the a16z crypto fund.

a16z crypto is a $350M venture fund dedicated to investing in crypto companies and protocols. The fund is designed to include the best features of traditional venture capital, updated to the modern crypto world.

Every successive wave of technology presents an opportunity to design the metrics that will best forecast its health and success. Crypto is unique in this regard because of the wealth of publicly available data sources (e.g. peer-to-peer network traffic, transactions on blockchains, and events on smart contracts).

We are looking for a creative, self-directed Data Scientist with a passion for crypto (though not necessarily a lot of experience in the space) who will work closely with the investment team to help us:

  • Design and track the metrics that are most critical to understanding and forecasting the eventual success of all of the important crypto projects
  • Formulate the right questions about the space and specific projects that can be answered through data
  • Lead data analysis projects that answer those questions from start to finish: gather and process the necessary data, build and/or spin-up the adequate tools, and derive insights from the data
  • Distill and communicate those insights to the investment team through data visualizations, verbally and in writing (and even publish them to the broader community)
  • Grow into a leader and potentially build a team of data scientists and developers


Minimum Qualifications:
  • Strong background in quantitative discipline (e.g. computer science, mathematics, physics, statistics, electrical engineering, industrial engineering, etc)
  • Relevant multi-year work experience in data analysis or related field (e.g., as a computer scientist / software engineer / statistician / data scientist)
  • Experience with statistical software (e.g., R, Python, Julia, MATLAB, pandas) and database languages (e.g., SQL)
  • Experience articulating business questions and using mathematical techniques to arrive at an answer using available data
  • Experience translating analysis results into business recommendations
  • Demonstrated skills in selecting the right statistical tools given a data analysis problem
  • Demonstrated effective written and verbal communication skills
  • Demonstrated leadership and self-direction
  • Demonstrated willingness to both teach others and learn new techniques

Preferred Qualifications:
  • 4 years of relevant experience including applied machine learning and statistical methods
  • Applied experience with machine learning on large datasets
  • Applied experience with system simulation

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