Data Scientist

Role overview

In this position, you will work closely with business stakeholders to identify priorities and practical use cases, then design and deliver solutions using data science and Generative AI to create measurable business impact.

What you will do

• Partner with business users to understand priorities and use cases, then shape data science and GenAI solutions that support business goals.
• Explore new and emerging AI/data science approaches and recommend relevant methods for EDB to evaluate and adopt, such as agentic systems, LLMs, predictive modeling, fraud and anomaly detection, text analytics, and customer segmentation.
• Carry out data preparation work, including cleaning, preprocessing, and feature engineering.
• Support the day-to-day running and upkeep of deployed data science models and products, including Assistants on PAIR and AIBots.
• Build backend APIs and services that enable AI model deployment and system integration.
• Create frontend interfaces and user experiences for AI-driven applications.
• Maintain documentation for product updates and changes.
• Investigate and implement remediation for reported security weaknesses.

Requirements

• A bachelor’s degree in Computer Science, Computer Engineering, Machine Learning, Data Science, AI, or a closely related field is required.
• You should be able to understand and apply AI/ML methods for regression and classification problems.
• Hands-on familiarity with common Python libraries such as pandas, matplotlib, scikit-learn, XGBoost, NLTK, and spaCy is expected.
• You need a solid grasp of LLM fundamentals, including context windows, embeddings, chunking, token handling, and architectures such as RAG.
• Experience with context engineering and prompt optimization techniques is needed.
• Strong working knowledge of git and SQL is required.
• You should be comfortable using business intelligence platforms such as Tableau, Qlik, MS Power BI, and MicroStrategy.

Bonus experience

• Exposure to modern programming languages such as TypeScript and C#.
• Experience working with cloud platforms and services, ideally AWS.
• Practical knowledge of Docker and Kubernetes.
• Experience with web frameworks and full-stack development, including backend tools like FastAPI, Flask, or Express.js, REST APIs, and frontend technologies such as React, Vue.js, HTML/CSS, and TypeScript.
• Familiarity with LLM frameworks like LangChain, LlamaIndex, and Hugging Face Transformers.
• Understanding of vector databases and embedding methods such as Pinecone, Chroma, and FAISS.
• Knowledge of AI agent frameworks and multi-agent architectures.
• Strong presentation skills, with the ability to explain technical ideas clearly to non-technical audiences.
• Experience with statistical tools such as R and SAS.

Privacy notice

Any personal information shared during the application process will be handled in accordance with the applicable data protection laws and the company’s Privacy Notice.