Senior Data Scientist

• Add value by finding data solutions that fit the business problems we want to solve for our customers
• Own and evolve our classical ML/NLP enrichment pipeline (matching, classification, embeddings) and the services that power all our data applications
• Design, build, and run LLM-based components in production, such as enrichment, classification, and entity matching, with prompt design treated as part of system design
• Choose the right tool for the problem: a state-of-the-art model, an LLM, a classical algorithm, or a smart business rule, weighing accuracy, cost, and latency
• Define evaluation methods and quality metrics so LLM and ML output can be trusted at the same bar as our rule-based systems, together with our data engineers
• Look beyond the pure data science scope: work together with our data engineers to get POCs into production
• Write production quality code
• Identify new opportunities in the large amount of data we collect every day in our data lake
• Collaborate with business and data stakeholders to align requirements and expectations
• Drive continuous improvement in our data science setup
• Foster a collaborative and enjoyable team environment through code reviews, knowledge sharing, and daily interactions

Benefits

• 33 days holiday, including public holidays, plus the option to buy or sell five days each year (tbc)
• Company pension scheme (for full-time roles)
• Travel allowance
• Life Insurance
• Medical insurance
• Bonus

• Experience with Spark, preferably PySpark
• Experience with AWS or Azure cloud services, including model hosting
• Solid experience with embeddings and NLP, such as semantic similarity, entity matching, or text classification
• Ability to communicate in English, verbally and in writing
• Bachelor’s and/or Master’s degree in a quantitative field (e.g. data science, computer science, artificial intelligence)
• Result-driven and hands-on attitude
• 5+ years of experience as a Data Scientist
• Hands-on, practical experience bringing LLMs into production: prompt design, evaluation, and cost/latency tradeoffs, not just experimenting in a notebook
• Proactive and courage to speak up
• Experience with Python (sklearn, numpy, pandas, etc.)
• Experience with AI agent frameworks or computer vision is a plus
• Knowledge of and experience with machine learning algorithms, such as clustering, classification, and regression
• Eager to challenge the status quo and experiment with new tools and methods