Data Analyst TG Quality Foundations

Job Description

The Data Analyst creates rich experiences based on analyzing players' interests and needs, a person who excels by analyzing and recommending improvements to the user experience on consoles, mobile platforms and the Web on an Agile team.

The main tasks are:

• Identify relevant sources of information to gather, analyze and check data quality and results.
• Communicate the results of the data by highlighting important information for decision-making.
• Build an action plan and work with respective teams to implement and follow up selected recommendations.
• Identify, publish and continually improve the building and communicating of KPIs and other analyses.
• Draft reports and prepare dashboards.
• Create new processes and automate, standardize and optimize existing processes.
• Build analytical models to test various scenarios to determine recommendations to put in place.
• Work with various stakeholders (community managers, marketing, monetization, production, technical operations) to help them make decisions and guide the studio's strategic actions by providing a quantitative logic for potential decisions.
• Perform all other related duties.

Mandate : 

• KPIs for Director-Level Decision Making (50%):
  • Collaborate with product management teams & CPIs to understand strategic objectives and key priorities (ability to clarify & quantify our impacts in production | engines| partners).
  • Identify and define key performance indicators (KPIs) at the director level that align with overall production | engines | partners goals and QF product management objectives.
  • Develop reporting mechanisms to provide regular updates on KPIs, enabling directors to make informed decisions.
  • Continuously assess and refine KPIs based on changing user dynamics and organizational needs.
• TGQF Strategic data for production & partners (50%): 
  • Help delivering a set of metrics to evaluate the effectiveness of engineering processes with a specific focus on quality.
  • Implement tools and systems to automate the collection and reporting of quality engineering metrics.
  • Collaborate with cross-functional teams to ensure alignment of quality metrics with overall organizational objectives.