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o9 Global Data Science

Mondelez International

o9 Global Data Science

full-timePosted: Aug 4, 2026Updated: Sep 3, 2026Brazil, São Paulo

Job Description

Job DescriptionAre You Ready to Make It Happen at Mondelēz International?Join our Mission to Lead the Future of Snacking. Make It With Pride.You will be crucial in supporting our business by creating valuable, actionable insights about the data, and communicating your findings to the business. You will work with various stakeholders to determine how to use business data for business solutions/insights.How you will contributeYou will:Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization. In this role you will also formulate hypotheses and test them using math, statistics, visualization and predictive modelingUnderstand business challenges, create valuable actionable insights about the data, and communicate your findings to the business. After that you will work with stakeholders to determine how to use business data for business solutions/insightsEnable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications. Coordinate with other technical/functional teams to implement models and monitor resultsApply mathematical, statistical, predictive modelling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional dataDevelop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracyEvaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire. Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision makingContribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvementsWhat you will bringA desire to drive your future and accelerate your career and the following experience and knowledge:Strong quantitative skillset with experience in statistics and linear algebra.A natural inclination toward solving complex problemsKnowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from itKnowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and consKnowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc.Good communication skills to promote cross-team collaborationMultilingual coding knowledge/experience: Java, JavaScript, C, C++, etc.Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc. Ability to use data visualization tools to showcase data for stakeholdersMore about this roleYou will be a member of the Mondelēz Global o9 Data Science Team which is a global supply chain analytics organization and is responsible for all advanced statistical forecasting needs globally.The main objective of the role is to improve Sales Forecast Accuracy, its explainability and drive adoption of holistic forecasting.Job DescriptionYou will:You will work closely with Regional Data Science Teams located in US, LA and India, IT Team to set standards for tools, platforms and infrastructure for demand forecastingContribute to the creation and review of a cross-functional, enterprise-wide approach and culture for analytics and contribute to the development of analytics policy, standards and guidelinesBuild relationships with external experts and other advanced IT organizations to maintain knowledge of technological advancements and trendsManage the introduction and use of analytics to meet business requirements, ensuring consistency across all user groups. Also, you will establish and manage functional analytics methods, techniques and capabilities to enable the function to analyze data, generate insights, create value and drive decision making while you measure the progress of initiatives and market successes to the organizationAssess the business problems to be solved and what internal or external data sources to use or acquireIdentify and establish the veracity of the external sources of information that are relevant to the operational needs of the enterpriseDefine business-oriented goals for initiative(s) and explain the initiative(s) to business managersContribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvementsWhat you will bringA desire to drive your future and accelerate your career. You will bring experience and knowledge in:Experience in working on Demand Planning related projects and programsUnderstanding of processes within Demand Planning that link to forecast generation and its consumptionStrong experience in relevant areas including Data Science, Data Analytics, Big Data, Cloud Computing, Machine Learning (time can include relevant degree studies)At least 5 years of experience creating statistical/ML models on sales data including simulation and/or forecasting, deep understanding of strategic decisions needed to be taken to create a good demand forecast and provide consistent explanation (XAI)Strong quantitative background in statistics and linear algebra as well as programming knowledge (Python)Hold a MSc/PhD in a Data Science field such as Mathematics, Economics, Business or a related field. Strong experience in forecasting, segmentation and optimization algorithmsUnderstanding of XAI methods and their application in real-life scenariosFamiliarity generating dashboards and manipulating data visualization software KPIs/dimensionsExperience in solving Supply Chain business problems through Data Science – with focus on Demand PlanningVery good experience in forecasting for large FMCG companies with deployment to production using advanced and scalable architecturesWorking knowledge of o9 is a big plus No Relocation support availableBusiness Unit SummaryAt Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. That means delivering a broad range of delicious, high-quality snacks that nourish life's moments, made with sustainable ingredients and packaging that consumers can feel good about.We have a rich portfolio of strong brands globally and locally including many household names such as Oreo, belVita and LU biscuits; Cadbury Dairy Milk, Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. We are proud to hold the top position globally in biscuits, chocolate and candy and the second top position in gum.Our 80,000 makers and bakers are located in more than 80 countries and we sell our products in over 150 countries around the world. Our people are energized for growth and critical to us living our purpose and values. We are a diverse community that can make things happen—and happen fast.Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.Job TypeRegularData ScienceAnalytics & Data Science

Locations

  • Brazil, São Paulo
  • Mexico, Santa Fé

Skills Required

  • statisticsintermediate
  • statistical programming languages including Rintermediate
  • advanced statistical techniquesintermediate
  • working on Demand Planning related projectsintermediate
  • relevant areas including Data Scienceintermediate
  • forecastingintermediate
  • o9 is a big plusintermediate

Required Qualifications

  • A desire to drive your future and accelerate your career and the following experience and knowledge: (experience)
  • Strong quantitative skillset with experience in statistics and linear algebra. (experience)
  • A natural inclination toward solving complex problems (experience)
  • Knowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from it (experience)
  • Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and cons (experience)
  • Knowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc. (experience)
  • Good communication skills to promote cross-team collaboration (experience)
  • Multilingual coding knowledge/experience: Java, JavaScript, C, C++, etc. (experience)
  • Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc. Ability to use data visualization tools to showcase data for stakeholders (experience)
  • A desire to drive your future and accelerate your career. You will bring experience and knowledge in: (experience)
  • Experience in working on Demand Planning related projects and programs (experience)
  • Understanding of processes within Demand Planning that link to forecast generation and its consumption (experience)
  • Strong experience in relevant areas including Data Science, Data Analytics, Big Data, Cloud Computing, Machine Learning (time can include relevant degree studies) (experience)
  • At least 5 years of experience creating statistical/ML models on sales data including simulation and/or forecasting, deep understanding of strategic decisions needed to be taken to create a good demand forecast and provide consistent explanation (XAI) (experience, 5 years)
  • Strong quantitative background in statistics and linear algebra as well as programming knowledge (Python) (experience)
  • Hold a MSc/PhD in a Data Science field such as Mathematics, Economics, Business or a related field. Strong experience in forecasting, segmentation and optimization algorithms (experience)
  • Understanding of XAI methods and their application in real-life scenarios (experience)
  • Familiarity generating dashboards and manipulating data visualization software KPIs/dimensions (experience)
  • Experience in solving Supply Chain business problems through Data Science – with focus on Demand Planning (experience)
  • Very good experience in forecasting for large FMCG companies with deployment to production using advanced and scalable architectures (experience)
  • Working knowledge of o9 is a big plus (experience)

Responsibilities

  • Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization. In this role you will also formulate hypotheses and test them using math, statistics, visualization and predictive modeling
  • Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business. After that you will work with stakeholders to determine how to use business data for business solutions/insights
  • Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications. Coordinate with other technical/functional teams to implement models and monitor results
  • Apply mathematical, statistical, predictive modelling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data
  • Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy
  • Evaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire. Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision making
  • Contribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvements
  • You will work closely with Regional Data Science Teams located in US, LA and India, IT Team to set standards for tools, platforms and infrastructure for demand forecasting
  • Contribute to the creation and review of a cross-functional, enterprise-wide approach and culture for analytics and contribute to the development of analytics policy, standards and guidelines
  • Build relationships with external experts and other advanced IT organizations to maintain knowledge of technological advancements and trends
  • Manage the introduction and use of analytics to meet business requirements, ensuring consistency across all user groups. Also, you will establish and manage functional analytics methods, techniques and capabilities to enable the function to analyze data, generate insights, create value and drive decision making while you measure the progress of initiatives and market successes to the organization
  • Assess the business problems to be solved and what internal or external data sources to use or acquire
  • Identify and establish the veracity of the external sources of information that are relevant to the operational needs of the enterprise
  • Define business-oriented goals for initiative(s) and explain the initiative(s) to business managers
  • Contribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvements

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