Data Science Manager

Posted Yesterday
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2 Locations
Hybrid
Senior level
Big Data • Food • Hardware • Machine Learning • Retail • Automation • Manufacturing
We're a global snacking company empowering people to snack right.
The Role
As a Data Science Manager, you will analyze data using statistical and machine learning techniques, derive actionable insights, coordinate with stakeholders, and improve decision-making processes.
Summary Generated by Built In
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
What you need to know about this position:
Support, optimize, and ensure adherence to IBP and S&OE processes across the region's Business Units. Actively coordinating regional data consolidation, monitoring BU compliance with established standards, providing direct internal advisory and training, and collaborating with cross-functional teams to drive continuous improvement in planning processes and tools.
Job specific requirements:
  • 5+ years of experience in Supply Chain Planning, Demand Planning, Supply Planning, or IBP/S&OE roles.
  • Practical experience participating in or supporting IBP/S&OE cycles within a corporate environment.
  • Familiarity with process documentation, standard operating procedures, and training delivery.
  • Experience working with planning systems (e.g., SAP APO, SAP IBP, o9, Kinaxis) and data analysis tools (e.g., Excel, Power BI).
  • Fluency in English is required for effective regional interaction.

No Relocation support available
Business Unit Summary
Wacam is Mondelēz International's Latin America presence with more the 1700 wonderful people proudly representing a diversity of cultures and nationalities. Wacam includes 13 countries: Colombia, Ecuador, Perú, Chile, Bolivia, Panamá, Costa Rica, Nicaragua, Honduras, Guatemela, El Salvador, República Dominicana, Puerto Rico. We make and distribute our global brands and local jewels such as Field, Club Social to over 190 million consumers.
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.
At Mondelez International we work under a hybrid model, in which our offices at WACAM offer us a space for connection, collaboration and co-creation, with attendance being subject to the needs of the teams themselves and/or the business.
Where permitted by internal policies and local laws, new hires are required to be fully vaccinated with the COVID-19 vaccine as a condition of employment by their date of hire, unless they are granted a medical accommodation.
Job Type
Regular
Data Science
Analytics & Data Science

Top Skills

C
C++
Excel
Java
JavaScript
Kinaxis
O9
Power BI
Python
R
Sap Apo
Sap Ibp
SQL
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The Company
HQ: Chicago, IL
90,000 Employees
Year Founded: 2012

What We Do

Mondelēz International, Inc. (NASDAQ: MDLZ) is an American multinational confectionery, food, and beverage company based in Illinois which employs approximately 90,000 individuals around the world. Our Purpose Our purpose is to empower people to snack right. We will lead the future of snacking around the world by offering the right snack, for the right moment, made the right way. Our Brands We’re leading the future of snacking with iconic brands such as Oreo, belVita and LU biscuits; Cadbury Dairy Milk, Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. Our People Our 90,000+ colleagues around the world are key to the success of our business. Our Values and Leadership Commitments of Love our Consumers and Brands, Grow Every Day, and Do What's Right shapes our culture – what we believe in, stand for, and what guides our actions and decisions. Great people and great brands. That’s who we are. Our Strategies We are uniquely positioned to lead the future of snacking with strong leadership in our categories, an unparalleled portfolio of global and local brands, and a solid footprint in fast-growing markets. Aimed at delivering sustainable growth, our strategic plan is centered around three strategic priorities: • Growth: accelerate consumer-centric growth • Execution: drive operational excellence • Culture: build a winning growth culture

Why Work With Us

We offer passionate, energetic and curious people a huge choice of careers in our fun, fast-paced, global business. We operate in four regions: Asia, Middle East & Africa; Europe; Latin America; and North America. And in over 80 countries our people are united in a common purpose to empower people to snack right.

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Mondelēz International Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

#TeamMDLZ F​lexible Work​ing Pledge: We Trust each other to work flexibly and productively We show Empathy, encouraging belonging and connection We are Mindful of making space and taking time

Typical time on-site: Flexible
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