Principal Data Scientist
Zynga - San Francisco, CA

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Zynga’s mission is to connect the world through games. Each day millions of users spend time with one or more of Zynga’s games on Facebook, and their mobile phones. To realize our mission we need to understand our players and their behavior in order provide them with the best gaming experience. We focus on areas such as Machine Learning, Data Mining, Statistics and Large Graph Analysis.
We are looking for a Senior Data Scientist with experience in solving large-scale practical Machine Learning problems. You will be working closely with game teams to identify and formalize problems around user modeling and user experience. You will be responsible for designing and implementing models and algorithms for new problems in Social Gaming and work with the game teams to put those models into production in our games. You will have the opportunity to have impact on the fun that millions of players have every day in Zynga’s network.

Work with large amounts of data to identify opportunities that would help improve the experience that Zynga provides to its players
Apply Machine Learning and Data Mining techniques for a variety of user modeling tasks within Zynga’s Game Network.
Work closely with game teams to design, test, verify and implement Machine Learning techniques with Zynga’s games that impact the daily life of millions of users
Design and evaluate novel approaches to experiments for gameplay

MSc/PhD in Computer Science, Electrical Engineering, Math or Statistics
At least 5 years of experience in solving real-world practical problems using Machine Learning
At least 5 years of experience on mining and modeling large-scale data (hundreds of terabytes)
Extensive in-depth knowledge of Data Mining, Machine Learning, Algorithms
Knowledge of at least one high-level programming language (C++, Java)
Knowledge of at least one scripting language (Perl, Python, Ruby)
Knowledge of SQL and experience with large relational databases
Knowledge of at least one ML toolset (R, Weka, KNIME, Octave, Mahout, scikit-learn)
Strong ability to formalize and provide practical solutions to research problems
Strong communication skills and ability to work independently to get an idea from inception to implementation.

Knowledge of the state of the art in at least one of Bayesian Optimization, Recommendation Systems, Social Network Analysis, Information Retrieval
At least 5 years of experience with storing, sampling, querying large-scale data (hundreds of terabytes) and experimentation frameworks
At least 5 years of experience with Hadoop, Spark, Mahout or Giraph