At Glu Mobile, we build free-to-play mobile games. Our titles include Covet Fashion, Design Home, Deer Hunter, MLB Tap Sports Baseball, and Disney Sorcerer's Arena, to name a few. These games, and the marketing efforts to acquire players for these games, generates lots of data. We use these data to form relationships with existing and potential players and to build better games. One of the core challenges we face is organizing these data into high fidelity tables and dashboards for analysts throughout the company to use. We are expanding our Business Intelligence team to meet this challenge. Our goal is to reduce the effort required to use our data for rigorous decision making. 

As a BI Analyst, you will work in a cross-functional pod of engineers and analysts. Analysts and decisions makers throughout the company will look to you for guidance on accessing, interpreting, and improving the data we use for decision making. You will construct dimensional modeling tables, build dashboards, and teach others how to use them. Further, you will work with your teammates to maintain data quality standards and take steps to address quality issues. This is highly visible role that will require you to interact with each of the game studios and our finance team.

You’ll most often:

• Consult with analysts and decision makers 
• Apply statistical concepts to aggregate discrete data
• Construct high-performance tables and views 
• Build and maintain dashboards 
• Pull and summarize data with traditional and big data tools 
• Design and analyze A/B, multivariate, and natural experiments 

You’ll be a great fit for this role if you have:

• Passion for games and empathy for our players
• Excitement for working in a data rich environment 
• Enthusiasm for using analytical techniques to answer business problems 
• Experience working in Unix-like and cloud environments 
• Experience in tracking down (and collaboratively fixing!) data discrepancies that are bound to arise in complex, interconnected data warehousing systems 
• Experience in helping QA teams create relevant unit and system-wide checks on reporting & analytics tooling

Bonus points for:

• Master’s degree in quantitative field such as statistics, computer science, or related field 
• Experience delivering analytics driven consulting 
• Writing re-usable code in dynamic programming languages (such as Python) or statistical programming environments (such as R or Julia) 
• Collaborating on code using Git