Manager, Data Science (GenAI Lead)

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

About the Role

We are seeking a highly motivated and experienced Senior Data Scientist to join our team and spearhead the development of Generative AI (GenAI) capabilities within Mondelēz International from an enterprise application perspective. In this pivotal role, you will champion the full lifecycle of GenAI application projects, taking ownership from initial concept and design to successful deployment, ongoing optimization, and continuous improvement. Beyond project execution, you will serve as a strategic advisor, guiding the evolution of our GenAI capabilities and ensuring alignment with overarching business objectives. This includes defining and enforcing internal standards for GenAI application development, guaranteeing compliance with ethical and security guidelines. You will also support the design of enterprise-level logical architectures for typical GenAI applications, and evaluate and recommend the most appropriate tools and technologies to empower our GenAI initiatives. Ultimately, you will play a critical role in shaping the future of GenAI within Mondelēz, driving innovation, maximizing value realization, and fostering responsible AI adoption across the enterprise. 

Key Responsibilities: 

• GenAI Application development: Serve as the tech lead from data science point of view in the complete lifecycle of GenAI application projects, from initial ideation and design to successful deployment, optimization, and continuous improvement. Include both in house development or partner collaboration. 

• Strategic Advisory: Provide strategic advice on the evolution of our GenAI capabilities to match company goals. Keeping up with the latest GenAI trend and map that to Mondelez application context to enable us do things better and smarter. 

• Standards and Governance: Help establish and enforce programmatic approaches, governance frameworks and best practices for effective GenAI application building. Responsible AI for GenAI applications, data protection in GenAI context, complying to regulatory requirements and cost-effective GenAI application deployment. 

• Enterprise Architecture Support: Support the design and development of enterprise-level logical architectures for typical GenAI applications, ensuring scalability, maintainability, and integration with existing infrastructure.  

• Technology Evaluation and Recommendation: Evaluate and recommend the most appropriate GenAI tools, technologies, and platforms to empower our GenAI initiatives, staying abreast of the latest advancements in the field with a focus on cloud-based tools/technologies. 

• Knowledge Sharing and Mentoring: Share knowledge and expertise with other team members, mentor junior data scientists, and spearhead the development of a strong GenAI community within Mondelēz. 

 

Skills and Experiences: 

• Deep understanding of data science methodologies and implications: proficiency in machine learning, deep learning, statistical modelling, optimization, causal inference etc. Experience in mapping business problems to such methodologies with clear understanding/consideration in Ethical implications, risk mitigation, integration requirements, resource demand/optimization etc.  

• Hands-on experience in cloud environment (8 years): Cloud platform, cloud-based data storage, processing, AI/ML model building, model life cycle, process orchestration, cost optimization etc. 

• Working experience with MLOps (5 years): Understand MLOps processes and practice, familiar with MLOps Tools and technologies. Contributed significantly to shaping MLOps practice in an enterprise setup. 

• LLM Application architecture & Integration (3 years): Hands-on experience building RAG applications, clear understanding of the underline technologies. Extensive experience integrating LLM into workflow through different ways (API etc). Experience in build Agent to leverage LLM and other tools for complex tasks. Familiar with Agent frameworks and orchestration tools. 

• Core GenAI expertise (3 years): Prompt Engineering, Agentic Framework, Model fine-tuning.

• Cloud Based Deployment & Scaling (LLM-Specific): Practical experience deploying and scaling LLM-based applications in cloud environment. Familiar with scaling strategies for LLMs, and integration with other application. 

• Collaboration with cross-functional teams (5 years): Proven ability to collaborate effectively with cross-functional teams. Excellent communication skills, both written and verbal to articulate technical concepts. 

Qualifications: 

• Master’s degree in a Quantitative Discipline, PhD preferred. 

• Minimum 12+ years of experience in data science/AI.

• Minimum 3 years of GenAI focused experience.​

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