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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 help our business react to changing business conditions with excellent data analysis. You will define the requirements, perform the analysis and identify patterns in large amounts of data.

How you will contribute

You will:

  • Define requirements for analysis in a given business area and perform detailed analysis and identify trends defined in the requirements
  • Identify patterns and help the business react to changing business conditions
  • Perform root-cause analysis and interpret data
  • Work with large amounts of data such as facts, figures, and mathematics/formulas and undertake analytical activities and delivers analysis outputs in accordance with customer needs and conforming to established standards
  • Understand and be involved with aspects of the data science process
  • As the investigator on the data science team, you will apply your knowledge of languages and pull data out of SQL databases, using Tableau/Power BI type tools, and producing basic data visualizations and reporting dashboards

What you will bring

A desire to drive your future and accelerate your career and the following experience and knowledge:

  • Knowledge of Microsoft Excel, Power BI, SQL,R, Python, SAS software, Google Analytics, Google Tag Manager, Tableau, Google AdWords, statistical software
  • Moderate knowledge in math and statistical skills, strong business acumen, moderate computer science/coding skills
  • Develop key performance indicators and create visualizations of the data
  • Utilize business intelligence and analytics tool

More about this role

What you need to know about this position:

  • Utilize mathematical, statistical, computer science, machine learning, and data visualization methods to analyze data and extract valuable insights. In this role, you will formulate hypotheses and test them using mathematical, statistical, visualization, and predictive modeling approaches.
  • Grasp the business challenges at hand, generate actionable insights from data, and effectively communicate your findings to the business. Subsequently, collaborate with stakeholders to determine how to leverage business data for solutions and insights.
  • Foster data-driven decision-making by creating custom models or prototypes based on discerned trends and patterns. Work closely with other technical and functional teams to implement these models and monitor their outcomes.
  • Apply mathematical, statistical, predictive modeling, or machine-learning techniques while being mindful of their inherent limitations. Select, acquire, and integrate data for analysis, develop data hypotheses and methods, train and evaluate analytics models, share insights and findings, and continuously refine the process with additional data.
  • Develop processes, techniques, and tools for analyzing and monitoring model performance, all while ensuring data accuracy.
  • Assess the necessity for analytics, evaluate the problems to be solved, and determine the appropriate internal or external data sources for use or acquisition. Specify and apply suitable mathematical, statistical, predictive modeling, or machine-learning techniques to analyze data, unearth insights, create value, and support decision-making.
  • Contribute to the exploration and experimentation in data visualization and oversee evaluations of the benefits and value of analytics techniques and tools, while also recommending enhancements.

Delivering projects being part of a global team

What extra ingredients you will bring:

A desire to drive your future and accelerate your career and the following experience and knowledge:

  • Possesses a robust quantitative skill set, along with a background in statistics and linear algebra.
  • Demonstrates a natural aptitude for tackling intricate problems.
  • Familiarity with statistical programming languages like R, Python, SQL, and others, for data processing and insights extraction.
  • Knowledge of machine learning techniques, including decision-tree learning, clustering, artificial neural networks, with an understanding of their advantages and disadvantages.
  • Competence and experience in advanced statistical concepts and techniques, encompassing regression, distribution properties, statistical testing, and more.
  • Effective communication skills for fostering collaboration across teams.
  • Proficient in multilingual coding, including Java, JavaScript, C, C++, among others.
  • Expertise and familiarity with statistics and data mining techniques such as random forest, GLM/regression, social network analysis, text mining, and the ability to utilize data visualization tools to present insights to stakeholders.

Programming languages including R, Python, SQL, etc., to process data and gain insights from it. Experience in Cloud platform including Databricks is a plus

Education / Certifications:

Masters Degree preferred. Minimum of a bachelors degree 

Job specific requirements:

  • A strong aptitude for developing extensive personalization and recommendation algorithms, as well as a grasp of information retrieval and ranking algorithms.
  • Familiarity with both Deep Learning and traditional Machine Learning, encompassing CNN and RNN architectures, Reinforcement Learning, and Graph Neural Networks, among others.
  • Hands-on experience with one or more Deep Learning frameworks, such as TensorFlow and PyTorch, is preferred.
  • Prior research involvement in the fine-tuning and application of large language models.
  • Proficiency in Python or R programming is a must.
  • Competence in working with relational databases, SQL, and NoSQL databases is expected.
  • Previous experience with unstructured data like images and text is considered a valuable asset.
  • Strong communication skills and the ability to effectively convey complex technical concepts to diverse audiences, from data scientists to engineers and business partners, are essential.

Travel requirements:

10%

Work schedule:

Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy

Business Unit Summary

At 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 Type

Regular

Data Science

Analytics & Data Science

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