Identify & 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 responsibilities*:
- identify and prioritize global challenges and use cases for hr analytics
- approach 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 initiatives
- stay on top of trends and solutions
- work with stakeholders to develop questions and hypotheses to provide insight into hr matters
- develop hr analytics solutions to support hr teams in decision-making & interactions with their stakeholders
- conduct complex data analysis, and identify patterns and trends
- advance 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 network
- generate the space to share best practices, needs, challenges and ideas
- coordinate global hr analytics network (coe, ohr & regions)
- provide transparency on best practices & use cases (int.
& ext.)
*position challenges*:
- understanding 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.
*qualifications*:
- *languages 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 analytics
- *areas of expertise*: 5-7 years in hr data management, data analysis, or a related field.
- *technical skills*:
- *programming languages*:proficiency in python
- *data 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.
- *statistical analysis*: a strong foundation in statistics to interpret data and drive insights.
- knowledge of big data platforms and cloud services
- *soft skills*: strong management skills.
the ability to engage with various stakeholders and communicate complex data concepts in a clear manner
*internal/external relations*:
internal
- p&it
- regional hr
- other central areas
*cemex diversity and inclusion statement*:
at cemex, we recognize the diversity of the world in which we live and in which we do business.
we respect diversity, we address the inclusion and non-discrimination of any talented person, regardless of gender, physical ability, age, sexual orientation, culture, ethnicity, religion, political affiliation, marital status, pregnancy / maternity / paternity, and nationality.
we promote a culture of equity for the construction of a sustainable business and the well-being and development of cemex employees.