M03 - Data Scientist

Responsibilities Collaborating with business users to understand their key priorities and use cases; proposing and developing solutions using data science and/or Generative AI techniques to drive business value Data wrangling & analysis - preprocessing, cleaning and feature engineering Supporting the daily operations and maintenance of deployed data science models and products, including Assistants on PAIR / AIBots Developing backend APIs and services to support AI model deployment and integration Building frontend interfaces and user experiences for AI-powered applications Documenting changes to existing products Reviewing and implementing fixes for reported security vulnerabilities; Researching emerging AI/data science techniques and identifying relevant ones for EDB to explore and adopt (e.g. Agentic, LLM, Predictive, Fraud/Anomaly Detection, Text Analytics, Customer Segmentation) Requirements To perform this role, you must have/ be: 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) Bonus skillsets which will allow you to excel 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)