Christopher Green

  • New York City
  • cmgreen210
  • cmgreen



Sr. Tech Data Scientist - Cortex | May 17 - Present

  • Trained deep neural networks for image recognition of nsfw content using Twitter's Torch-backed deep learning platform
  • Designed an ML media classification service that includes support for image and video processing, seamless model updating, and ongoing monitoring of model performance
  • Built and tested recurrent networks to predict certain types of toxicity
  • Mentored and provided technical guidance to a summer intern who built data extraction pipelines that communicated with internal Twitter services
  • Added functionality to Cortex's AI platform code base in Python and Lua
  • Taught introductory machine learning classes to fellow Twitter employees

Sr. Data Scientist - Analytics | Nov 16 - May 17

  • Provide data science support to the Home Timeline team
  • Deployed production Scala code which performed A/B tests on the composition of users' ranked tweets
  • Analyzed user reading behavior by mining client event logs

Sr. Software Engineer - Vine | Jun 16 - Nov 17

  • Designed and built an Apache Spark powered Scala ML pipeline
  • Maintained a recommender system for millions of users and millions of videos
  • Researched models to predict abusive comments
  • Supported Vine's backend python REST API used by millions of clients

Rocket Fuel

Machine Learning Scientist | Aug 15 - May 16

  • Designed and built machine learning pipelines to place display and video ads in real-time
  • Contributed in Scala to the development of the company's ML pipeline used to train all production models
  • Researched novel ways to maximize client brand measures such as video completion rate and ad viewability
  • Utilized Apache Spark and Hadoop to process petabytes of data across thousands machines

Barclays Investment Bank

Quantitative Analyst, AVP | Mar 12 - Aug 14

  • Developed in and extensively supported a large-scale C++ analytics library including meeting weekly deadline production builds
  • Personally designed and implemented a multi-use extensible optimization library that included linear and non-linear optimization algorithms
  • Built functionality for automated portfolio hedging to control bank capital levels
  • Using Python, automated monthly builds of the bank interest rate curves to guarantee seamless business continuity
  • Coordinated with both front office and IT teams to ensure timely delivery of central counterparty margin replication production code based on VaR and expected shortfall risk measures used in front office and client applications

Summer Associate | May 11 - Aug 11

  • Researched margin optimization algorithms and optimal futures pricing
  • Presented findings to the Quantitative Analytics group at the conclusion of the program


Code: Scala, Python, Lua, C++

Machine Learning Frameworks: Tensorflow, Torch, Spark MLlib, scikit-learn

Big Data: Spark, Scalding, Hadoop/Hive

Math: Probability & Statistics, Numerical Analysis, Computational Geometry, Time Series Analysis, Stochastic Calculus


Stony Brook University | Aug 08 - Dec 11

Mathematics | PhD

  • Dissertation: The Ahlfors Iteration for Conformal Mapping
  • Research areas included conformal geometry and numerical conformal mappings

Cornell University | Aug 04 - Dec 07

Applied Mathematics | BS

  • Graduated magna cum laude

Zipfian Academy at Galvanize | Jan 15 - Apr 15

  • Extensive training in machine learning algorithms and applications including supervised and unsupervised techniques
  • Constructed a facial emotion video and image classifier using convolutional neural nets in GraphLab Create with GPU Acceleration
  • Hands-on work with scalable data technologies such as MapReduce, Spark, and AWS