Data Science Manager

Purpose of 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 Mondelz 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 Mondelz, 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 Mondelz.

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:

• Masters degree in a Quantitative Discipline, PhD preferred.
• Minimum 8 years of experience in data science/AI.
• Minimum 3 years of GenAI focused experience.