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

You 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 Description

You 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 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

What you will bring

A 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 programs

• Understanding of processes within Demand Planning that link to forecast generation and its consumption

• Strong 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 algorithms

• Understanding of XAI methods and their application in real-life scenarios

• Familiarity generating dashboards and manipulating data visualization software KPIs/dimensions

• Experience in solving Supply Chain business problems through Data Science – with focus on Demand Planning

• Very good experience in forecasting for large FMCG companies with deployment to production using advanced and scalable architectures

• Working knowledge of o9 is a big plus

Supporto alla Relocation disponibile?

Nessun supporto disponibile per la relocation

Riepilogo business unit

Alla Mondelēz International, la nostra missione è fornire ai consumatori lo snack giusto, al momento giusto, preparato nel modo giusto. Ciò significa offrire una vasta gamma di snack deliziosi e di alta qualità che nutrono i momenti della vita, realizzati con ingredienti e confezioni sostenibili per i quali i consumatori possono sentirsi bene.

Disponiamo di un’ampia gamma di forti marchi internazionali e locali, tra cui molti nomi rinomati come i biscotti Oreo, belVita e LU; il cioccolato Cadbury Dairy Milk, Milka e Toblerone; le caramelle Sour Patch Kids e la gomma da masticare Trident. Siamo orgogliosi di mantenere la prima posizione a livello globale nel business dei biscotti, cioccolato e caramelle e la seconda posizione per le gomme da masticare.

I nostri 80.000 produttori e fornai si trovano in oltre 80 paesi e vendiamo i nostri prodotti in oltre 150 paesi in tutto il mondo. Le nostre persone sono stimolate a crescere e sono fondamentali per vivere il nostro scopo e i nostri valori.

Siamo una comunità diversificata che può far accadere le cose e farle accadere velocemente.

Mondelēz International è un datore di lavoro che offre pari opportunità e tutti i candidati qualificati verranno presi in considerazione ai fini dell’impiego a prescindere da razza, colore della pelle, religione, sesso, orientamento o preferenza sessuale, identità di genere, origine nazionale, stato di disabilità, stato di veterano protetto oppure qualsiasi altra caratteristica protetta dalla legge.

Tipo di lavoro

Contratto a tempo indeterminato

Data Science

Analytics & Data Science