Data Scientist

About the role

AB InBev GCC’s Supply Analytics team builds data‑driven solutions to improve brewery efficiency. As a Data Scientist you will design and implement statistical and machine‑learning models, leveraging cloud and micro‑service architectures to deliver AI‑powered insights.

Key responsibilities

• Develop and fine‑tune Generative AI models, including large language models, to solve business problems.
• Design, implement, and optimise AI‑driven solutions that enhance automation, efficiency and decision‑making.
• Deploy and scale AI models on cloud platforms using micro‑services, Docker and Kubernetes.
• Apply DevOps and MLOps best practices for model serving, data and code versioning, and CI/CD pipelines.
• Collaborate with engineering, business and product teams to translate needs into AI solutions.
• Ensure model interpretability, reliability and performance while reducing bias.
• Build internal tools and utilities to improve team productivity and streamline workflows.
• Maintain high coding standards, including documentation, testing, logging and performance monitoring.
• Stay current with advances in Generative AI, LLMs and deep learning and incorporate innovative approaches.

Required profile

• Academic degree (Bachelors or Master’s) in Computer Science, Computer Applications, Engineering or related field.
• Minimum 3 years of relevant experience in data science or machine learning.

Required skills

• Python programming.
• Strong foundation in linear algebra, calculus, probability and statistics.
• Experience with supervised, unsupervised and reinforcement learning algorithms.
• Natural Language Processing techniques (tokenization, POS tagging, NER, machine translation).
• Large Language Model work: LangChain, fine‑tuning, prompt engineering.
• Data preprocessing (cleaning, normalization, augmentation, handling imbalanced datasets).
• SQL and NoSQL databases (MongoDB, Redis).
• Cloud platforms: Microsoft Azure and Google Cloud Platform.
• DevOps tools: CI/CD pipelines, Docker, Kubernetes.
• API development with FastAPI or Flask.