Senior Data Scientist

  • Location

    San Francisco

  • Sector:

    Data Science

  • Job type:


  • Salary:


  • Contact:

    Mia Monaghan

  • Contact email:


A trading start up are looking for a Data Scientist that will help us discover the information hidden in vast amounts of data, and help make smarter trading decisions. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems in the context of algorithmic selection/trading.


  • Selecting/creating features from raw data, and building/optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Extending the data used in modeling with third party sources of information
  • Processing, cleaning, and verifying the integrity of data used for analysis
  • Doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated data consistency checks (e.g. between live/historical data) and unit testing techniques to ensure ongoing model performance

Skills and Qualifications

  • Experience with supervised/unsupervised machine learning techniques, especially tree-based algorithms and k-means clustering. Neural networks experience is a plus, especially with RNNs and CNNs
  • Experience modeling and making sense of complex systems.
  • Advanced skills in Python- especially Pandas. Must be able to output code in Python at a rapid rate
  • Must have at least 4 years of coding experience. Doesn’t matter what language- applicant must have a strong underlying coding ability
  • Must have strong applied statistics skills, such as understanding of distributions, hypothesis testing, and probability
  • Must have a passion for trading/investing. Any past trading/investing experience, either personally or professionally, is a plus
  • Great communication skills and experience with data visualization tools in Python
  • Proficiency in SQL is a plus. Must be able to write basic queries at minimum
  • Experience with high performance computing is a plus (e.g. cluster computing on AWS with Spark/Hadoop)
  • Masters/PhD in a quantitative discipline is required