Job Description
Are 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 contribute
You 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 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
What you will bring
A 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 problems
- Knowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from it
- Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and cons
- Knowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc.
- Good communication skills to promote cross-team collaboration
- Multilingual 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 stakeholders
More about this role
We are looking for a Data Science Manager to lead strategic data initiatives, drive data-driven decision-making, and develop advanced analytical solutions that create business value.
What extra ingredients you will bring:
Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or related.
Solid experience in Data Science, Analytics, or Forecasting, with prior experience in a leadership or supervisory role.
Strong hands-on experience developing and applying statistical forecasting models, such as ARIMA, exponential smoothing, regression, and machine learning models.
Proficiency in data analysis tools and programming languages, including Python, R, and SQL, as well as experience with forecasting software.
Proven experience interacting with Senior Management.
Experience in market analysis; background in CPG (Consumer Packaged Goods) companies is a plus.
Fluent English (mandatory).
Advanced Spanish is a plus
Location: São Paulo, Vitória de Santo Antão or Curitiba – Hybrid model
We are aware of our role as transformation agents to generate positive change, so diversity, equity and inclusion are one of our priorities. We believe in breaking down stereotypes and barriers to ensure the representation of society within our company. And for that, we have a Diversity Committee that operates on four fronts, People with disabilities (PCD), Ethnic-Racial, Women and LGBTQIAP+, in addition to being part of MOVER – Movimento pela Equidade Racial.
Mondelez International is attentive to the future of work and values the well-being of our people, seeking to provide the best experiences. Therefore, some of our administrative vacancies are eligible for the hybrid model, allowing remote work on certain days of the week.



No Relocation support available
Business Unit Summary
Mondelēz Brasil is Mondelēz International’s fourth largest operation in the world, with approximately 7,500 employees proudly producing, selling and distributing some of the most beloved brands of chewing gum, candies, powdered beverages, cream cheeses, chocolates, cookies and desserts in Brazil. We make the Brazilians’ favorite products such as Bis, Lacta, Oreo, Club Social, Sonho de Valsa, Trakinas, Trident, Halls, Royal, Tang and many others. We are truly part of the lives of Brazilians: You can find our mouth-watering products in more than 700,000 points of sale and we are present in more than 92% of Brazilian homes. Our factories are located in Vitória de Santo Antão, in the state of Pernambuco, and Curitiba, in the state of Paraná. We are also home to one of the company's 11 technology centers around the world, responsible for research and development, so we can continue to create new and innovative products, offering the right snack for the right time, done in the right way.
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 Type
Regular
Data Science
Analytics & Data Science