Data Scientist

• Our Operations Platform team leads the development of automated workflows and tools for our Operations and Customer Support staff to achieve an amazing customer experience
• To achieve this, we recognise that data isn’t just a resource - it’s a cornerstone
• Plan and execute the roadmap for your services together with the team
• Play a pivotal role in designing the architecture of your data products, ensuring they are scalable, robust, and synergistic with our existing platforms
• Research, build, test and deploy models - this is where you will spend most of your time. With a focus on team ownership, this gives a lot of time for our developers and data scientists to actually work technically instead of with process
• Once deployed, you will continue to oversee your products, monitoring their performance metrics and making data-driven adjustments as needed to optimise result

At least 5 years of end-to-end data science and software engineering experience, preferably in a dynamic environment with a modern tech stackRecent hands-on experience in deploying and maintaining an AI agent/workflow powered by LLMs, using both low level SDKs (openai, anthropic, google-genai,..) and prompt engineering frameworks (llama-index, langchain, dspy, ..)Experience with applying a wide variety of machine learning techniques to business problems, particularly with tabular and natural language dataExperience working in Operations, specifically significant experience in customer service automationsStrong command of SQL, Python together with its scientific stack (numpy, pandas, matplotlib, scikit-learn)Good understanding of Software Engineering practices (e.g. test-driven development, OOP, CI/CD, etc.) and experience with productionizing ML productsGeneral understanding of LLMOps

principles, for evaluating, testing, versioning and experimenting prompts in staging and production (langsmith, langfuse, arize-phoenix, lunary, ..)