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 ML
A natural inclination toward solving complex problems
Knowledge / experience with statistical programming languages including SAS, R, Python, SQL, etc., to process data and gain insights from it
Knowledge of machine learning techniques including decision-tree learning (Random Forest, Gradient Boost) 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
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
What you need to know about this position :
The 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 Statistical 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
Propose additional data elements which we can consume and work with ETL developer to get those into SAS staging and SAS ABTs
Run demand-supply segmentation analysis as per defined frequency
Education / Certifications
Either of the following is applicable as educational criteria for the position :
Degree / Masters in quantitative field of Statistics, Applied Mathematics or Engineering, with specific full-time courses in Analytics
Certifications any of SAS Base, SAS VF, SAS Visual Statistics, etc
Strong Applied Knowledge of analytical techniques in statistical modelling, machine learning with exposure to forecasting domain especially driver based forecasting
Experience on working with FMCG, Food & Beverages, Retail or similar industry data with understanding the business process with be advantage
Should be able to articulate data science outcome into business understandable language
Fluent English, other European languages would be an 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, however for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy