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Open nowPosted today

Global Supply Planning Data Science Manager

mdlz626 open roles

Where
India Remote
Work mode
Remote
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Your applicationOpen nowGlobal Supply Planning Data Science Managermdlz · India Remote

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The clock on this job

Early applications get read.

9.8% of postings close within 7 days. Measured by our own scanner across the market. mdlz postings stay open a median of 7 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.9%3 days
  3. 9.8%7 days
  4. 15.6%14 days
  5. 33.8%30 days
This job: posted today

mdlz median: 7 days open

The posting

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

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