About the job

At Pflegia we are building and operating an innovative job-matching platform, which intelligently brings together caregivers and healthcare employers. Our vision is to become Europe's leading job platform for nursing professions and to fight the nursing crisis! Become part of the team and shape the nursing job market together with us!

About The Role

We're looking for a Data Scientist who treats AI as a working tool, not a buzzword. You'll sit at the intersection of statistics, machine learning, and product: building predictive models, improving our LLM- and RAG-based systems, and running experiments that directly shape how our platform matches supply and demand. Your work won't end at a slide deck. You'll define the metrics, ship the analysis, and follow through until the impact shows up in the numbers.

Tasks

• Build, validate, and ship statistical and predictive models that directly inform pricing, matching, and growth decisions
• Develop and improve LLM-powered features, from retrieval-augmented generation (RAG) pipelines to applications of new AI technologies that open up product innovation
• Own the reliability of our AI features: design prompt and evaluation workflows, measure output quality, and catch regressions before users do
• Turn open questions into testable hypotheses and design experiments (e.g., A/B tests) that give clear, decision-ready answers
• Dig into funnels and user journeys to find drop-offs and friction points, and quantify where supply and demand can be better matched
• Team up with performance marketing to sharpen targeting, attribution, and campaign efficiency with data
• Define the KPIs that matter, build the dashboards and monitoring behind them (AWS QuickSight), and make business impact visible and measurable
• Keep your work transparent and traceable: document, prioritize, and communicate progress in Jira across product, engineering, and marketing
• Present findings to stakeholders as concrete recommendations, then stay involved until they're implemented

Requirements

• You love to work with data: explore it, model it, improve its quality.
• Deep grounding in statistics: you know which method fits which problem and can defend your assumptions, not just run the library defaults
• Fluent in Python (pandas, scikit-learn, NumPy) and SQL, with a track record of applying them to real business problems rather than toy datasets
• Hands-on experience taking ML and modern AI techniques from idea to a working solution that someone actually uses
• Practical experience with LLMs and RAG systems in production or near-production settings, including prompting, retrieval quality, and output evaluation
• Solid command of A/B testing: sample sizing, significance, common pitfalls, and knowing when an experiment is the wrong tool
• Working knowledge of performance marketing concepts such as CAC, ROAS, and attribution logic
• Project experience in at least one of: anomaly detection, trend analysis, marketing mix modeling, or multi-touch attribution
• Background in e-commerce, marketplaces, or other platform-based businesses, ideally with exposure to supply and demand dynamics
• Bonus: degree in mathematics, statistics, physics, computer science, or a related quantitative field

Benefits

• Flat hierarchies with short decision-making paths (start-up mentality) and an open corporate culture with helpful & communicative colleagues
• Regular feedback conversations
• A pleasant workplace (open-plan office centrally located in Berlin-Mitte) with home office option
• A very nice and cooperative working atmosphere
• Free drinks

• Build, validate, and ship statistical and predictive models that directly inform pricing, matching, and growth decisions
• Develop and improve LLM-powered features, from retrieval-augmented generation (RAG) pipelines to applications of new AI technologies that open up product innovation
• Design prompt and evaluation workflows, measure output quality, and catch regressions before users do
• Design experiments, including A/B tests, that give clear, decision-ready answers
• Analyze funnels and user journeys to identify drop-offs and quantify supply-and-demand matching opportunities
• Work with performance marketing to improve targeting, attribution, and campaign efficiency
• Define KPIs and build dashboards and monitoring in AWS QuickSight
• Document, prioritize, and communicate progress in Jira across product, engineering, and marketing
• Present findings as concrete recommendations and follow through until they are implemented

• Python
• pandas
• scikit-learn
• NumPy
• SQL
• Statistics
• Predictive modeling
• Machine learning
• LLMs
• Retrieval-augmented generation (RAG)
• Prompting and output evaluation
• A/B testing and experiment design
• Performance marketing
• CAC, ROAS, and attribution
• Anomaly detection, trend analysis, marketing mix modeling, or multi-touch attribution
• AWS QuickSight
• Jira

• Deep grounding in statistics and ability to select appropriate methods and defend assumptions
• Fluency in Python (pandas, scikit-learn, NumPy) and SQL, with experience applying them to real business problems
• Hands-on experience taking ML and modern AI techniques from idea to a working solution
• Practical experience with LLMs and RAG systems in production or near-production settings
• Solid command of A/B testing, including sample sizing, significance, and common pitfalls
• Working knowledge of performance marketing concepts such as CAC, ROAS, and attribution logic
• Project experience in at least one of anomaly detection, trend analysis, marketing mix modeling, or multi-touch attribution
• Background in e-commerce, marketplaces, or other platform-based businesses is preferred
• A degree in mathematics, statistics, physics, computer science, or a related quantitative field is a bonus