Senior Data Scientist(J103181)

ML Solution Design & Deliver

• ◆ Design and implement machine learning solutions aligned with business requirements and data technology roadmap
• ◆ Independently drive end-to-end delivery of ML projects, from data processing to model deployment
• ◆ Select appropriate modeling approaches and engineering solutions for different use cases

Model Engineering & System Implementation

• ◆ Develop, optimize, and deploy machine learning models into production environments
• ◆ Build and maintain model inference services and data pipelines
• ◆ Ensure system reliability, scalability, and performance for ML applications

Technical Execution & Exploration

• ◆ Conduct PoC independently to evaluate new approaches and technologies (e.g., LLM
• applications)
• ◆ Continuously improve model performance and engineering efficiency
• ◆ Stay up to date with emerging AI/ML technologies and apply them when appropriate

Collaboration & Communication

• ◆ Work closely with business stakeholders and cross-functional teams to translate requirements into technical solutions
• ◆ Communicate technical concepts effectively in business-friendly language
• Provide technical support for multiple internal use cases
• ◆ Oversees training and development of partners directly and indirectly managed and makes
• effective staffing decisions.
• ◆ Provides coaching, direction and leadership support to team members in order to achieve
• partner, business and customer results.
• ◆ Strong programming skills in Python
• ◆ Strong experience with machine learning frameworks (e.g., scikit-learn, XGBoost, PyTorch)
• ◆ Solid knowledge of data processing and feature engineering (pandas, numpy)
• ◆ Proficiency in SQL and experience with relational databases
• ◆ Experience deploying ML models or building inference systems in production
• ◆ Experience with LLM applications (e.g., RAG, prompt engineering, LLM integration)
• ◆ Experience in retail / catering / consumer-related industries
• ◆ Knowledge of time-series forecasting or attribution modeling
• ◆ Familiarity with distributed data processing or big data frameworks
• ◆ Experience with visualization tools (Tableau, Power BI)
• ◆ Familiar with Git and standard software development practices