.Job DescriptionIdentify & conduct Global HR analytics: Descriptive, Diagnostic, Predictive & Prescriptive (incl. AI)Coordinate Global HR Analytics Network (CoE, OHR & Regions)Provide transparency on best practices & use cases (Int. & Ext.)Main ResponsibilitiesIdentify and prioritize global challenges and use cases for HR AnalyticsApproach to identify and prioritize opportunities where Analytics bring value: Descriptive, Diagnostic, Predictive & Prescriptive (including use of Artificial Intelligence)Translate business needs into HR analytics requirements (Data Translator between HR & Data Science team)Create and maintain updated a Global Roadmap of HR Analytics initiativesStay on top of trends and solutionsWork with stakeholders to develop questions and hypotheses to provide insight into HR mattersDevelop HR Analytics solutions to support HR teams in decision-making & interactions with their stakeholdersConduct complex data analysis, and identify patterns and trendsAdvance local use of Artificial Intelligence in HR (Predictive, Descriptive, Machine Learning, and Gen AI)Responsible for designing and developing advanced business intelligence (BI) solutions that enable organizations to extract insights and value from their data. (e.G. Headcount, KPI's)Activate HR Analytics NetworkGenerate the space to share best practices, needs, challenges and ideasCoordinate Global HR Analytics Network (CoE, OHR & Regions)Provide transparency on best practices & use cases (Int. & Ext.)Position ChallengesUnderstanding the various aspects of HR that can benefit from analytics, such as recruitment, employee engagement, performance management, and retention strategies. It requires a deep understanding of HR processes and the ability to identify where analytics can add value.Collaboration with Centers of Excellence, Operational HR, and regional teams to ensure alignment and sharing of best practices and use cases.Providing transparency on best practices and use cases: Maintain a clear and open channel of communication regarding the successes and learnings from analytics initiatives to foster a culture of continuous improvement and innovation.QualificationsLanguages needed & proficiency:Spanish and English: Advanced proficiency, with the ability to communicate effectively in a business environment.Academic Background: A bachelor's degree in fields such as Computer Systems, Digital Transformation, Data Science or Engineering. Master in Data AnalyticsAreas of Expertise: 5-7 years in HR data management, data analysis, or a related field.Technical Skills: Programming Languages: Proficiency in PythonData Management and Visualization: Experience with SQL for database management, and tools like Power BI or Tableau for data visualization.Machine Learning Libraries: Familiarity with libraries such as scikit-learn, TensorFlow, or PyTorch for implementing machine learning models