Global Supply Planning Data Science Manager

Mondelēz International

. Analyze and derive value from data using mathematics, statistics, computer science, machine learning, and data visualization .

Posted 10/15/2026full-timeRemote • India, PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong quantitative skills in statistics and linear algebra, with proficiency in statistical programming languages such as R, Python, and SQL. Capable of developing and implementing machine learning models and data visualization techniques to derive actionable insights for business decision-making.

Highest-signal resume keywords

Statistical Programming LanguagesMachine Learning TechniquesData Visualization ToolsAdvanced Statistical TechniquesQuantitative Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

StatisticsLinear AlgebraPredictive ModelingData Mining TechniquesRegression AnalysisDecision-Tree LearningClusteringArtificial Neural NetworksText MiningSocial Network Analysis

Soft Skills

Good Communication SkillsCross-Team Collaboration

Tools & Technologies

RPythonSQLJavaJavaScriptCC++

Certifications & Qualifications

Bachelor's DegreeMaster's Degree

Industry Keywords

Data AnalysisData VisualizationModel Performance MonitoringData-Driven Decision MakingBusiness Insights

Tech Stack

Tools & technologies

JavaJavaScriptPythonSQLC++

About the role

Key responsibilities & impact

Analyze and derive value from data using mathematics, statistics, computer science, machine learning, and data visualization
Formulate and test hypotheses using mathematics, statistics, visualization, and predictive modeling
Understand business challenges and create actionable data insights
Communicate findings to business stakeholders and determine how business data can support solutions and insights
Create custom models or prototypes from trends and patterns to enable data-driven decision making
Coordinate with technical and functional teams to implement models and monitor results
Select, acquire, and integrate data for analysis
Develop hypotheses and methods, train and evaluate analytics models, share insights, and iterate with additional data
Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy
Evaluate analytics needs, assess problems, identify data sources, and apply appropriate analytical techniques
Explore and experiment with data visualization
Manage reviews of analytics techniques and tools and recommend improvements

Requirements

What you’ll need

Strong quantitative skillset with experience in statistics and linear algebra
Knowledge/experience with statistical programming languages including R, Python, SQL, etc.
Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, and their pros and cons
Knowledge and experience in advanced statistical techniques and concepts including regression, distribution properties, and statistical testing
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, and text mining
Ability to use data visualization tools to showcase data for stakeholders
Bachelors /Master's degree
Travel might be required

Benefits

Comp & perks

Travel might be required
No Relocation support available