Advanced Data Analyst

1 week ago


Montreal, Quebec, Canada Electronic Arts Inc. Full time
About the Role

We are seeking a highly skilled and experienced Advanced Data Analyst to join our team at Electronic Arts Inc. as a key member of our data analytics department.

Key Responsibilities
  • Business Needs Analysis: Translate business requirements into actionable data analytics projects to inform strategic decision-making.
  • Data Analytics Process: Oversee the entire data analytics process, from data collection to implementing data-driven recommendations.
  • Predictive Modeling: Develop and implement predictive and prescriptive analytic models to identify trends and opportunities.
  • Subject Matter Expertise: Act as a subject matter expert in advanced analytics, providing mentorship to junior analysts and stakeholders.
  • Machine Learning: Spearhead the design and implementation of complex machine learning models and algorithms to tackle business challenges.
  • Data-Driven Insights: Provide data-driven insights and recommendations to senior leadership, playing a key role in strategic decision-making.
  • Team Leadership: Lead cross-functional teams in the development and implementation of strategic data projects, ensuring alignment with overall company objectives.
  • Process Improvement: Innovate new data analysis methodologies and tools for improved efficiency and accuracy.
  • Data Governance: Establish and enforce data governance protocols to ensure data integrity, security, and compliance.
  • Tool Selection: Evaluate and aid in selecting tools, technologies, and platforms for data analysis and machine learning.
  • Culture Development: Advocate for a data-driven culture across the organization, fostering a deeper understanding and appreciation for the value of data and analytics.
  • Telemetry System: Design and implement a robust, reliable, and highly effective telemetry system that accurately collects and transmits crucial in-game data, enhancing game performance and user experience.
  • Integration: Ensure seamless integration of the telemetry system with each studio's game systems, guaranteeing compatibility and optimal performance.
  • Data Pipeline: Develop and maintain a high-capacity data pipeline for efficient handling, processing, and analysis of the collected telemetry data, ensuring data integrity, security, and accessibility.
  • Analysis and Research: Perform various analyses/researches based on the requests and characteristics received from users/clients, so that they can define the specifications necessary to develop/update/improve the informatic systems.
Requirements
  • Effective Communication: Understand and address effectively to queries from teams and partners, championing the application of new concepts and improvements.
  • Advanced Statistical Analysis: Apply advanced statistical analysis to craft insightful reports for stakeholders and partners with top management to define data analysis objectives.
  • Data Science Techniques: Utilize expert Data Science techniques to scrutinize and analyze data, with a comprehensive understanding of descriptive statistics for data aggregation and summarization.
  • Data Analysis Projects: Oversee and manage data analysis projects, creating forecasting models, and examining trends for strategic decision-making purposes.
  • Machine Learning Solutions: Supervise the creation and administration of machine learning solutions, guaranteeing the production of superior, optimized algorithms.
  • Technical Scripts: Draft complex technical scripts, standardize data values for data analytics systems, and assess new data analysis tools and technologies.
  • Data Complications: Proactively investigate data complications and work on rectifying them while tracking critical performance indicators.
  • Data Cleaning and Mapping: Head the data cleaning, mapping, and shaping processes and deliver intricate data insights in a clear, effective manner.
  • Stakeholder Communication: Articulate clearly with all stakeholders, understanding and ensuring adherence to organizational data policies and structures.
  • Business Process Improvement: Systematically identify and direct the implementation of business process improvements, contributing to strategic planning at an executive level.
  • Collaboration: Suggest and execute solutions with minimal supervision, actively engaging in cross-discipline collaborations.
  • Communication and Feedback: Authors and revises various materials, explaining intricate statistical concepts in an easy-to-understand language for non-technical stakeholders.
  • Data Visualization: Direct the design and execution of data visualization strategies, ensuring expedited decision-making and continuous improvement within the data analysis function.
  • Task Management: Manage tasks effectively, identifying problems early, and employing past experiences and creativity to problem-solving.
  • Feedback and Coaching: Give and welcome constructive feedback, coaches team members, and manages his/her own time efficiently.
  • Tool Selection and Management: Coaches junior and senior analysts in choosing suitable tools for data extraction and analysis, ensuring efficient dataset management.
  • Recruitment and Selection: Participate in and often lead recruitment and selection processes for new team members.
  • Collaboration with Cross-Functional Teams: Cooperate with different internal and external cross-functional teams to comprehend their future needs in terms of KPIs, and then architect and develop the telemetry system to align with those KPIs;
  • Game Development and Design: Work closely with game developers and designers to comprehend the game mechanics, player behavior, and adjust the implementation process around those areas;
  • Implementation and Data Aggregation: Oversees the implementation process and the data aggregation / pipeline creation to ensure that all necessary data is accurately captured and properly formatted to answer future questions;
  • Testing and Debugging: Cooperate with the QV team to test telemetry under different scenarios and ensure it correctly triggers and collects data. Assists with debugging and develops workarounds to overcome any issues or limitations that may arise during the implementation phase;
  • Data Privacy and Protection: Guarantees data privacy and protection guidelines to comply with current regulation;
  • Telemetry System Maintenance: Maintains and improves telemetry systems.

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