Data Scientist

• Extract, transform, and analyze large-scale structured and unstructured datasets using Python, SQL, and cloud-based technologies.
• Perform exploratory data analysis (EDA), data preprocessing, feature engineering, and model development to address business challenges.
• Develop, evaluate, optimize, and deploy machine learning models, including predictive, classification, and forecasting solutions.
• Build and maintain scalable data and machine learning pipelines for production environments.
• Develop AI-powered solutions using Generative AI technologies, including Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and Agentic AI concepts.
• Monitor model performance, conduct model validation, and implement continuous improvement initiatives to ensure accuracy and reliability.
• Apply statistical analysis and experimentation techniques to identify insights and support data-driven decision-making.
• Translate analytical findings and model outputs into actionable business recommendations.
• Collaborate with Product Owners, Business Stakeholders, Data Engineers, and other cross functional teams to deliver impactful solutions.
• Document data science methodologies, model assumptions, and technical approaches to support knowledge sharing and governance.
• Follow software engineering best practices, including version control, testing, and code quality standards.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Strong programming skills in Python and SQL.
• Hands-on experience with data science and machine learning libraries such as Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow/Keras, PyTorch, or similar.
• Solid understanding of Machine Learning algorithms, statistics, feature engineering, model evaluation, and experimentation methodologies.
• Experience working with time-series forecasting, predictive analytics, classification models, and imbalanced datasets.
• Familiarity with data processing frameworks such as Spark or PySpark.
• Understanding of MLOps concepts, CI/CD pipelines, Git, APIs, and model deployment practices.
• Experience working with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of Generative AI concepts, including LLMs, RAG architectures, embeddings, prompt engineering, and AI agents.

Sysco LABS is the Global In-House Center of Sysco Corporation (NYSE: SYY), the world’s largest foodservice company. Sysco ranks 56th in the Fortune 500 list and is the global leader in the trillion-dollar foodservice industry.

Sysco employs over 75,000 associates, has 337 smart distribution facilities worldwide and over 14,000 IoT-enabled trucks serving 730,000 customer locations. For fiscal year 2025 that ended June 29, 2025, the company generated sales of more than $81.4 billion.

Sysco LABS Sri Lanka delivers the technology that powers Sysco’s end-to-end operations.

Sysco LABS’ enterprise technology is present in the end-to-end foodservice journey, enabling the sourcing of food products, merchandising, storage and warehouse operations, order placement and pricing algorithms, the delivery of food and supplies to Sysco’s global network and the in-restaurant dining experience of the end-customer.