As a Data Scientist you’ll combine data science and Generative AI techniques to create innovative models and products that support areas such as investment promotion, industry development, and corporate functions. You’ll collaborate closely with teams across the organization to uncover business challenges, shape technical solutions, and deliver AI and Machine Learning tools that make a real impact.
What you’ll do:
Work with business users to understand their priorities and use cases, then design and build data-driven and AI-powered solutions that add measurable value.
Stay curious about emerging AI and data science trends—such as agentic systems, LLMs, predictive modeling, anomaly detection, text analytics, and customer segmentation—and explore how they can be applied within the organization
Get hands-on with data through wrangling, cleaning, and feature engineering to prepare high-quality inputs for your models.
Help maintain and optimize deployed models and products, including Assistants on PAIR and AIBots, ensuring they run smoothly day-to-day.
Develop backend APIs and services to integrate AI models into existing systems.
Build user-friendly interfaces and experiences for AI-driven applications.
Keep documentation updated as products evolve.
Review and address any reported security vulnerabilities to maintain product integrity.
To do well in this position, you’ll need:
• Minimum of Bachelor’s Degree in Computer Science, Computer Engineering, Machine Learning / Data Science / AI or related disciplines;
• Able to understand and apply a range of AI/ML techniques for regression and classification
• Familiar with popular python packages ( e.g. pandas, matplotlib, scikit-learn, XGBoost, NLTK, spaCy )
• Understanding of LLM concepts (e.g. context windows, embeddings, chunking, token management) and architectures (e.g. RAG)
• Experience with context engineering techniques and prompt optimization strategies
• Proficient in git, SQL
• Proficient in Business Intelligence tools (e.g. Tableau, Qlik, MS PowerBI, Microstrategy)
Complementary skillsets that contribute to success in this role include:
• Proficient in modern programming languages (e.g. typescript, C#)
• Experience in cloud platform and services preferably in AWS
• Experience in Docker/Kubernetes
• Experience with web frameworks and full-stack development, including backend frameworks (e.g. FastAPI, Flask, Express.js) and RESTful API development, and frontend technologies (e.g. React, Vue.js, HTML/CSS, TypeScript)
• Experience with LLM frameworks (e.g. LangChain, LlamaIndex, Hugging Face Transformers)
• Knowledge of vector databases and embedding techniques (e.g. Pinecone, Chroma, FAISS)
• Understanding of AI agent frameworks and multi-agent systems
• Strong presentation skills and ability to explain technical concepts clearly to a non-technical audience
• Proficient in statistical software tools (e.g. R, SAS)
