Senior Data Scientist

• Work on end-to-end Data Science and Machine Learning projects, from problem definition and data exploration to model development, deployment, and performance monitoring.
• Translate complex business problems into scalable analytical, machine learning, and AI solutions that deliver measurable business value.
• Design and develop advanced machine learning models, including forecasting, predictive analytics, classification, recommendation systems, anomaly detection, and deep learning solutions.
• Development and deployment of Generative AI applications using LLMs, RAG architectures, prompt engineering, Agentic AI frameworks, NLP techniques, and workflow orchestration tools.
• Own model lifecycle management, including training, deployment, monitoring, explainability, validation, governance, and performance optimization.
• Design and implement scalable cloud-based data science and AI solutions across AWS, GCP, Azure, or equivalent platforms.
• Perform advanced statistical analysis, experimentation, feature engineering, forecasting, and root-cause analysis to enhance model accuracy and business outcomes.
• Develop and maintain high-quality, reusable, and well-tested code following engineering best practices.
• Technical troubleshooting and resolution of complex data, model, and pipeline issues in production environments.
• Establish and promote best practices in data science, machine learning engineering, MLOps, and AI governance.
• Collaborate with business stakeholders, product teams, engineering teams, and leadership to define roadmaps and technical strategies.
• Mentor junior Data Scientists and contribute to knowledge sharing, onboarding, code reviews, and technical leadership within the team.
• Communicate technical concepts, insights, risks, assumptions, and recommendations effectively to both technical and non-technical audiences. *

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 2-4 years of experience in Data Science, Machine Learning, AI, or related analytical disciplines.
• Advanced expertise in Python and strong proficiency in SQL. * Strong knowledge of Machine Learning, Statistical Modelling, Deep Learning, Feature Engineering, and Model Evaluation techniques.
• Experience building and deploying production-scale machine learning solutions.
• Expertise in forecasting, time-series modelling, predictive analytics, anomaly detection, and advanced analytics techniques.
• Hands-on experience with machine learning frameworks such as Scikit-learn, XGBoost, TensorFlow, PyTorch, Prophet, DeepAR, or equivalent.
• Strong understanding of MLOps practices, including CI/CD, model deployment, monitoring, governance, and automation.
• Experience with workflow orchestration and data engineering tools such as Airflow, Spark, PySpark, and ETL/ELT frameworks.
• Experience with cloud platforms such as AWS, GCP, or Azure, including cloud-native ML and data services.
• Strong knowledge of Generative AI technologies

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.