Prinicpal Data Scientist
Zynga is a leading developer of the world’s most popular social games that are played by millions of people around the world each day. To date, more than 1 billion people have played our games across Web and mobile, including FarmVille, Zynga Poker, Words With Friends, Harry Potter: Puzzles & Spells, Merge Dragons!, Empires & Puzzles, Hit it Rich! Slots, Toy and Toon Blast, and CSR Racing.
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 continually strive to better understand our players and provide them with experiences that surprise and delight them.
Here’s where you would come in: as a member of the Central Analytics team, you will join a multidisciplinary team of Analysts and Data Scientists that builds groundbreaking technology for all of Zynga’s games and business functions. We want you to identify and formalize projects aimed at improving the user experience in our games, then use our state-of-the-art and ever-evolving tech stack to build and implement your solutions. Be innovative, be creative, use every bit of our 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. You will collaborate with Product Managers, Game Designers, and Engineers to deliver business impact. And, change current practices in line with new findings and insights.
Leverage our modern tech stack, AWS (Redshift & Kinesis), Databricks and PySpark, Airflow, and Tableau to identify opportunities to improve the experience that Zynga provides to its players
Apply predictive modeling 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 models with Zynga’s games that impact the daily life of millions of users
Design and evaluate novel scalable approaches to experiments for gameplay, using our in-house experimentation platform
Specifically, you may encounter projects focused on: Using Bayesian methodologies for predicting user behavior under uncertainty, predicting game feature efficacy through simulation, or personalizing game features using recommendation algorithms.
Required Skills and Experience:
BS in Computer Science, Math, Statistics, Economics, or other quantitative fields; Masters or PhD strongly preferred
5+ years of work experience in data science, machine learning, or analytics roles
Demonstrated experience with some or all of the following: machine learning, data mining, predictive modeling, statistics, experimental design, computational analytics, econometric modeling, data visualization
Fluent in Python, SQL, and other programming languages; Experience in applying machine learning on large datasets, preferably using Spark on Databricks
Strong written and oral communication skills
What we offer you:
Zynga Stock RSUs and Bonus Plan
Full medical, dental, vision benefits as well as life insurance
Generous Paid Maternity/Paternity leave
Open vacation policy for all full-time employees
Flexible working hours on many teams
Work alongside driven individuals towards a common goal
Zynga is an equal opportunity employer. We are proud of our diverse community; we do not discriminate on the basis of race, sex, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, medical condition, disability, or any other class or characteristic protected by applicable law. We welcome candidates, players, employees, and partners from all backgrounds. Join us!
Zynga will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law.
Zynga is committed to providing reasonable accommodation to applicants with disabilities. If you need an accommodation during the interview process, please let us know.