Principal Data Scientist
Zynga’s data science team uses our unique and expansive data to model and predict user behavior, making our games more personalized and more fun to play! We strive for a better understanding of our players which translates into challenges and features that delight them and increased social engagement within our games.
Here’s where you would come in: identify and formalize problems predicting user behavior. Then create and implement your models to find solutions. Be innovative, be creative, use every bit of that key commodity – data. Millions of people play Zynga games every day, so our data is tremendously rich and we have a lot of it!
We will rely on you to communicate your findings to your peers – both technical and non-technical. Your solutions will need to be demonstrably impactful and visual. You will work with our game teams to put your models into production.
We would like you to be able to:
- Work with large amounts of data
- Identify opportunities that would help improve the experience our players have with our games
- Apply predictive modeling techniques for a variety of user modeling tasks
- Work closely with game teams to design, test, verify and implement statistical models
- Design and evaluate novel approaches to experiments for gameplay
- Recognize that sometimes (If not most times) the simple solution is the best solution
- Coach and mentor Data Science team members
We love candidates who have:
- Advanced degrees in Computer Science, Math, Statistics, Economics, Astrophysics or other quantitative field; Masters or PhD strongly preferred
- At least 10 + years of experience working with some or all of the following: probability, statistics, data mining, predictive modeling, experimental design, computational analytics, econometric modeling
- 5+ years of experience managing Data Scientists and/or Analysts
- Experience designing, architecting and/or building environments and libraries to facilitate the production of data science and analytics
- Fluency in SQL
- Fluency in some or all of the following: R, Python, Spark (Or equivalent)
- An ability to work independently to get an idea from inception to implementation, including knowledge of techniques for validation and A/B testing
- Experience building deep relationships and the ability to integrate with their stakeholders
- Comfort working effectively in a fast-paced environment with changing priorities
- Comfort collaborating effectively across departments: engineers, product managers, analysts, business, and marketing functions
- A strong business acumen with a customer-first focus in their approach to data science
- A scrappy, action-driven ability to work autonomously
- Highly developed skills in data visualization
- Comfort with Hadoop
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