Live opening · Posted 1 day ago

Global Supply Planning Data Science Manager

Mondelēz International · India (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyMondelēz International
LocationIndia (Remote)
Work modeYes
SkillsPython, JavaScript, Java, C++
SourceLinkedin
ListedPosted 1 day ago

About the role

Description supplied by the original job listing.

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 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
Education / Certifications: Bachelors /Master's degree
Travel requirements: Travel might be required
No Relocation support available
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

Work arrangement
Yes

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