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
- Analyze and derive value from data through the application methods such as statistics, time series modelling, machine learning and data visualization.
- Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business.
- Develop data hypotheses and methods, train and evaluate forecasting models, share insights and findings and continue to iterate with additional data.
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 ML (Random Forest, Gradient Boost, etc.)
- Time series modelling experience is an advantage
- Knowledge/experience with statistical programming languages including SAS, SQL, etc., to process data and gain insights from it
- Good communication skills to promote cross-team collaboration
- Strong analytical and presentation skills
- Proactiveness, self-motivation and natural inclination toward problem solving
- Advanced English
What you need to know about this position:
The Intern/Junior Data Scientist forecasting will be responsible for advanced forecasting methodologies for demand forecasting to generate better forecasting results in terms of accuracy and bias
- Determine, create and maintain the best time series / machine learning models be to be used, by considering SKU demand behavior using segmentation strategy, to generate high quality demand statistical forecast with low forecast error and bias
- Collaborate with Demand Planners to identify right drivers and lever which influences demand and thus incorporate in statistical forecasting process
- Support SAS Implementation for market for demand modelling in SAS and SAS Model Forecast Improvement activity. Keep close liaison with SAS implementation partner to get transitioned process to Central Analytics Team
- Refine forecasting models, by reviewing forecast performance and incorporating feedback from the Demand Planner, to improve forecast error and bias metrics
- Analyze the model performance every month / week (Where MAPE is deteriorating etc) and post process the output and if required finetune the output
Education / Experience
- Student of or a Degree in quantitative field of Big data, Statistics, Econometrics, Computer Science or similar
- Certificates of SAS Base, SAS Viya, Pyspark etc, will be an advantage
- Experience on working with FMCG, Food & Beverages, Retail or similar industry data with understanding the business process with be advantage
The responsibilities of this position are performed within the framework of a regional business model that is defined and managed by Mondelēz Europe GmbH, Switzerland .
No Relocation support available
Business Unit Summary
At Mondelez Europe, we are proud, not only of the iconic brands we make, but also of the people who make them. Our delicious products are created in 52 plants across Europe by more than 28,000 passionate people. We are the top maker of chocolate and biscuits and a leading maker of gum and candy. We make sure our powerful global brands and local jewels like Cadbury
and Alpen Gold
biscuits, and Stimorol
gums get safely into our customers hands—and mouths. Great people and great brands. That’s who we are. Join us on our journey to continue leading the future of snacking around the world by offering the right snack, for the right moment, made 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.
Analytics & Data Science