Data Analyst

• Apply industry knowledge to come up with creative approaches to analyzing data and making project and studio improvements based on statistical methods.
• Lead complex analytics projects utilizing data warehousing, data architecture, fact and dimension tables, data modeling and ETL processes to extract and transform raw data through various standardization and cleansing techniques to develop structured and efficient data views in a scalable way using tools like SparkSQL, Python.
• Using advanced analytics techniques like statistical simulations and complex machine learning algorithms (logistic regression, boosted trees, random forest etc.) to generate valuable intelligence, predict player’s gaming behavior and find impacting factors, writing scripts in R/Python to evaluate feature performance pre-release using probabilistic distributions and rule-based machine learning systems.
• Extract and analyze complex data sets to understand game metrics in order to inform hypotheses, and to create analytical experiments with clear and measurable success goals.
• Perform ad hoc analysis as required to identify complex patterns affecting player behavior, measure feature performance and product health, support user acquisition and resolve data issues using R, Python, Excel and SparkSQL.
• Use data tools to identify and implement analytics and operational improvements in efficiency of repetitive data tasks, pipelines, processes both on project specific level and studio wide.
• Create, manage, and distribute data and insights via regular and ad-hoc reporting utilizing reporting and analysis platforms such as Tableau, Excel, SQL.
• Create reports summarizing business intelligence data for review by executives and managers; collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives.
• Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters in order to improve game performance
• Collaborate cross-functionally with other teams to communicate complex statistical findings and insights in business context to different teams and stakeholders for decision making.

Master’s degree, or its equivalent, in Business Statistics, Business Analytics, Data Science, Mathematics or related field, plus one (1) year of experience in business analytics, including:
1) data analytics applications;
2) statistical computing and data visualization;
3) predictive modeling; and
4) statistical learning methods for business decision‑making.