Data Scientist

October 10, 2026

Hybrid

Middle

Warsaw, Poznań

Worth knowing

Mandatory office attendance
English is required

Description

Data Scientist in the AI Function of a global healthcare digital technology team that builds platforms, tools and data science capabilities turning AI, GenAI and agentic ideas into real products. The role covers the full lifecycle from prototype to a monitored production capability, with a strong emphasis on evaluation, governance and rigorous experimentation. Day-to-day work includes production-ready coding, MLOps/LLMOps pipelines, LLM observability and close collaboration with product owners, engineers and business stakeholders

Responsibilities

Design and ship AI/ML solutions from prototype to a monitored capability, including next generation agentic AI systems that plan and execute complex multi-step work autonomously
Work closely with product owners, engineers and business stakeholders throughout the delivery
Turn ambiguous problems into clear modelling approaches and explain the trade-offs in language anyone can follow
Choose the right tool for the problem: classical model, fine-tuned model, retrieval over a foundation model or agentic workflow
Write clean, production-ready, reproducible code and help shape reusable patterns the wider team relies on
Bring rigour to every experiment with solid baselines, held-out testing and real error analysis
Build eval sets and harnesses for GenAI systems with golden datasets and regression checks for prompts
Statistically evaluate outputs for safety, reliability and consistency, offline and in production
Root solutions in real user feedback, not just lab results
Surface the cost, value, adoption and usage data that tells AI leadership what is working and where to invest next
Build within governance, security and compliance guardrails from day one of a project to the last
Help design checks that embed fairness, explainability and privacy into pipelines so they are enforced rather than aspirational
Share what you learn through reviews, demos and onboarding docs

Requirements

Hands-on expertise in data science and software engineering with Python, LLMs, RAG pipelines and agentic workflows
Ability to evaluate and fine-tune pre-trained models for domain use and design RAG and search/synthesis architectures
Strong NLP foundations: preprocessing, language modelling, sentiment analysis and NER
Solid core in statistics, model evaluation, feature engineering and standard algorithms
Real depth on vector embeddings, search theory, vector database selection and architecture, prompt and context engineering
Building MLOps/LLMOps pipelines for continuous deployment and monitoring, including observability for LLM systems: tracing, tokens, latency, cost telemetry, drift and hallucination monitoring
Forecasting and optimising infrastructure and API costs and managing platform vendor relationships to keep tools interoperable and secure
Comfort moving from strategic roadmap planning to solving ad-hoc technical problems, bridging non-technical stakeholders and technical implementation
Strong written and verbal English to explain technical trade-offs to technical and non-technical audiences alike
Preferred: hands-on experience deploying enterprise AI solutions on AWS or Azure, GCP exposure a plus
Preferred: model risk management, fairness and bias mitigation, transparency, explainability and data privacy
Preferred: pharma, healthcare or financial services background including GxP compliance and handling sensitive information

Conditions

Hybrid work model with employees in the Warsaw or Poznań office on average two days per week
Annual performance bonus with a target of 15% based on performance
Dedicated training budget for certifications, AI/tech courses and global conferences
Recharge Fridays: two additional paid Fridays off per quarter available to disconnect
Take Time Program: up to 3 months of sabbatical leave for any personal purpose
Flex Location: freedom to work remotely from different global locations for specified periods throughout the year
Take Time for Charity: up to 2 weeks of additional paid leave for volunteering initiatives
Private healthcare, group life insurance, MultiSport card and vacation subsidy
Stock share purchase program and yearly sales of company laptops and cars

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