Machine Learning Specialist_ Contract

• 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 • 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) • Datawrangling & analysis - preprocessing, cleaning and feature engineering • Supporting 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. Requirements • Minimum of a bachelor's degree in computer science, computer engineering, machine learning/data science/AI or related disciplines; • Able to tounderstand 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 optimisation strategies • Proficient in git, SQL • Proficiency in business intelligence tools (e.g., Tableau, Qlik, MS Power BI, Microstrategy)\ • Bonus skillsets which will allow you to excel in this role include: • Proficiency 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 • Proficiency in statistical software tools (e.g. R, SAS).