Data Scientist

Description

The team sits inside the company's digital technology group and builds the platforms, tools and data science capability that help teams turn AI, GenAI and agentic ideas into working products.

The work covers LLMs, enterprise data and orchestration, with a focus on agentic AI systems that reason, plan and act under human oversight.

The team is made of business-minded engineers who value ownership, rigour and visible impact. Your focus will shift with priorities, so you will work on a wide range of problems rather than one fixed area.

The role is based in Warsaw or Poznań on a hybrid model, with an average of two office days per week. Office days can change to fit needs such as workshops, conferences, town halls and team meetings.

Responsibilities

• Design and ship AI and ML solutions from prototype to a monitored capability, including agentic systems that plan and carry out multi-step work on their own. Work closely with product owners, engineers and business stakeholders throughout.
• Turn unclear problems into concrete modelling approaches and explain the trade-offs in plain language. Pick the right tool for each problem, whether a classical model, a fine-tuned model, retrieval over a foundation model or an agentic workflow, rather than defaulting to an LLM.
• Write clean, production-ready, reproducible code and help build the reusable patterns the wider team uses.
• Run every experiment with rigour: strong baselines, held-out testing and careful error analysis.
• Treat evaluation as a core skill. Build eval sets and harnesses for GenAI systems, maintain golden datasets and regression checks for prompts, and statistically assess outputs for safety, reliability and consistency, both offline and in production.
• Base solutions on real user feedback, not only on lab results.
• Use analytics to show AI leadership which cost, value, adoption and usage figures point to what works and where to invest.
• Work within the company's governance, security and compliance guardrails from the start of a project to the end.
• Help design checks that build fairness, explainability and privacy into pipelines so they are actually enforced.
• Share what you learn through reviews, demos and onboarding documents.

Requirements

• Hands-on experience in data science and software engineering, including Python, LLMs, RAG pipelines and agentic workflows. You are equally at home writing production code, designing system architecture and setting integration standards.
• Experience evaluating and fine-tuning pre-trained models for domain use, designing RAG and search or synthesis architectures, and building evaluation harnesses that statistically assess safety, reliability and consistency.
• Solid NLP skills, including preprocessing, language modelling, sentiment analysis and named entity recognition.
• A strong grounding in statistics, model evaluation, feature engineering and standard algorithms.
• Deep knowledge of vector embeddings, search theory, vector database selection and architecture, plus prompt and context engineering.
• Able to move between strategic roadmap planning and hands-on troubleshooting, and to bridge non-technical stakeholders and technical delivery.
• Able to build MLOps and LLMOps pipelines for continuous deployment and monitoring, including LLM observability (tracing, tokens, latency, cost telemetry, drift and hallucination monitoring).
• Able to forecast and optimise infrastructure and API costs and manage platform vendor relationships so tools stay interoperable, secure and future-proof.
• Strong written and spoken English, with the ability to explain technical trade-offs to both technical and non-technical audiences.
• A continuous learner who keeps up with a fast-moving field and enjoys sharing knowledge.
• Preferred: hands-on experience deploying enterprise AI solutions on AWS or Azure. GCP experience is a plus.
• Preferred: model risk management, fairness and bias mitigation, transparency, explainability and data privacy.
• Preferred: work in pharma, healthcare or financial services, including GxP compliance and handling sensitive information, plus awareness of emerging compliance standards for GenAI and foundation models.

Conditions

Salary range is 170,100 to 315,900 PLN per year on an employment contract (Umowa o Pracę), with a midpoint of 243,000 PLN. The final figure depends on skills, experience, qualifications and location.

The role may be eligible for a discretionary annual bonus with a 15% target, based on individual and company performance.

The company is an equal opportunity employer.

Benefits

• Annual performance bonus with a 15% target.
• Training budget for certifications, AI and tech courses, global conferences and different career paths.
• 2 extra paid Fridays off per quarter to fully disconnect.
• Sabbatical of up to 3 months for any personal purpose through the Take Time programme.
• Flexible location: work remotely from different global locations for set periods during the year.
• Up to 2 weeks of extra paid leave for volunteering.
• Private healthcare (LuxMed packages), group life insurance (UNUM), MultiSport card and vacation subsidy.
• Share purchase programme for company stock, and yearly sales of company laptops and cars.