Mondelēz International is looking to solve the problem of developing and growing their greatest asset - their people, by tapping into the vast stores of data at their disposal to inform talent decisions across key capabilities.
Requirements
- Proven experience (5-10 years) in workforce analytics, people analytics, or a similar role, with relevant experiences in data engineering, data analysis, statistical modeling (multi-variate statistical modeling, including approaches like linear and logistic regression, tree-based modelling), prompt engineering, LLM applications and data visualization principles.
- Strong knowledge of scope of work around data engineering, data modeling with statistical techniques, analytics use-case development, utilization of various business tools supporting the analytics domain.
- Proficient with programming languages used in data ingestion, manipulation, preparation, and statistical modeling (Python or R preferred), presentation tools (e.g., Power BI, Tableau).
- Proficient in applying generative AI techniques, including prompt engineering, to solve for use-cases in people analytics.
- Experience building people analytics applications using open-source LLMs is a significant plus.
- Working with a global team in multiple time zones, savvy, and comfort in working with remote team productivity tools such as Miro, Mural, Figma, JIRA, Monday, or Trello.
- Familiarity of Lean Six Sigma principles along with Kanban / Agile / Scrum Methodology a plus.
Responsibilities
- Consult with senior business leaders, HR COEs and HR field teams to provide data insights that inform our talent strategy, engagement practices, and inclusion programs.
- Partner with team’s analysts to drive analytical projects and deliver actionable insights.
- Conduct advanced statistical analysis, data modeling, and predictive analytics to identify trends, patterns, and correlations within the workforce data.
- Deliver insights with data storytelling visualizations.
- Deliver talent insights through applications of pay & labor market analysis, organizational network analysis, sentiment analysis, and time series forecasting applied in strategic workforce planning.
- Participate in executing a global workforce analytics strategic roadmap to globally operationalize and scale our workforce analytics capabilities to support business leaders and our HR community.
- Stay updated on industry best practices and emerging trends in workforce analytics, recommending innovative solutions to enhance data-driven decision-making.
Other
- Bachelor's degree in Statistics, Business Analytics, Data Science, Computer Science or a related Technology/Quantitative field. Master’s or PhD a plus.
- Strong business acumen and understanding of talent practices and processes.
- Exceptional communication skills, with the data story telling ability to present complex data and insights in a clear and concise manner to business audiences.
- Ability to work collaboratively and build strong relationships across various levels of the organization.
- Proven track record of driving data-informed decision-making and improving business outcomes through workforce analytics.
