Data Scientist - Recent PhD, Mentored Directly by a Master, Machine Learning, Quantitative Trading, Quant Lending Platform, Predictive Modeling, Logistic Regression, PFA, Clustering, R, Matlab, C/C++, Java, Python, Scala, Weka, Vowpal Wabbit - Dallas, TX

Our big data client in Dallas, Texas is seeking a Data Scientist to join their all PhD team, to be directly mentored by a master in quantitative trading, former head (SVP) of quantitative trading at the largest Wall Street trading institution for many years.  They apply machine learning techniques to very large data sets (multi-terabyte and petabyte scale).  Models can be predictive, descriptive, or both. This is an incredible beginner opportunity to work on real-time pricing engines, directional probability, market forecasts, international proxy pricing, pattern recognition, mortgage default predictions, capacity models, statistical arbitrage from a seasoned group of highly successful Wall Street professionals.

Primary Responsibilities:

  • Participate in the development of a quantitative platform for a lending institution
  • You will have exposure to quantitative trading through their money management and equities trading vertical, all Wall Street based

Qualifications:

  • Recent PhD graduate in Mathematics, Quantitative Analytics, Statistics, Finance, or a similar computational PhD degree
  • 0-1 year of experience in an academic, professional, or R&D organization
  • Experience developing predictive models using R, Matlab or similar modeling software
  • Experience with logistic regression, PFA, clustering and/or other quantitative models
  • Experience with machine learning algorithms such as Weka, Vowpal Wabbit or the like
  • Experience with programming in one or more of the following: C/C++, Java, Python, Scala, Clojure

Additional Qualifications:

  • Ability to hit the ground running
  • Independent thinker
  • Works well in a close-knit, team environment