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Roche

Global pharmaceuticals and diagnostics company

Data Scientist

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timePLN170.1k - PLN315.9k /yrHybrid

About the Job

Requirements

  • Hands-on expertise in data science and software engineering, including Python, large language models, retrieval-augmented generation pipelines, and agentic workflows.
  • Ability to write production code, design system architecture, and set integration standards.
  • Experience evaluating and fine-tuning pre-trained models for domain use.
  • Ability to design retrieval-augmented generation and search/synthesis architectures, build evaluation harnesses, and statistically evaluate outputs for safety, reliability, and consistency.
  • Strong natural language processing foundations, including preprocessing, language modelling, sentiment analysis, and named entity recognition.
  • Strong foundation in statistics, model evaluation, feature engineering, and standard algorithms.
  • Depth in vector embeddings, search theory, vector database selection and architecture, prompt engineering, and context engineering.
  • Ability to move between strategic roadmap planning and ad-hoc technical problem-solving, and bridge non-technical stakeholders with technical implementation.
  • Ability to build MLOps/LLMOps pipelines for continuous deployment and monitoring, including observability for large language model systems such as tracing, token usage, latency, cost telemetry, drift, and hallucination monitoring.
  • Ability to forecast and optimize infrastructure and API costs, and manage platform vendor relationships to keep tools interoperable, secure, and future-proof.
  • Strong written and verbal English, including explaining technical trade-offs to technical and non-technical audiences.

Responsibilities

  • Design and ship AI/ML solutions from prototype through monitored capabilities, including agentic AI systems that plan and execute complex multi-step work autonomously, working with product owners, engineers, and business stakeholders.
  • Translate ambiguous problems into clear modelling approaches, explain trade-offs in accessible language, and select an appropriate approach such as a classical model, fine-tuned model, retrieval over a foundation model, or agentic workflow.
  • Write clean, production-ready, reproducible code and help shape reusable patterns for the wider team.
  • Use solid baselines, held-out testing, and error analysis in experiments.
  • Build evaluation sets and harnesses for generative AI systems, use golden datasets and prompt regression checks, and statistically evaluate outputs for safety, reliability, and consistency offline and in production.
  • Root solutions in real user feedback.
  • Use analytics to surface cost, value, adoption, and usage data that informs AI leadership decisions and investment.
  • Build within Roche governance, security, and compliance guardrails throughout projects.
  • Help design practical checks that embed fairness, explainability, and privacy into pipelines.
  • Share learning through reviews, demos, and onboarding documentation.

Desired Qualifications

  • Hands-on experience deploying enterprise AI solutions on AWS or Azure; exposure to Google Cloud Platform is a plus.
  • Experience with model risk management, fairness and bias mitigation, transparency, explainability, and data privacy.
  • Experience in pharma, healthcare, or financial services, including GxP compliance and handling sensitive information, plus awareness of emerging compliance standards for generative AI and foundation models.

About the Company

Roche

Global pharmaceuticals and diagnostics company

Roche is a global leader in pharmaceuticals and diagnostics. It develops medicines and diagnostic tools that help detect, monitor, and treat diseases, using research and biotechnology to drive new therapies and tests. Roche combines drug development with in-house diagnostic products to support personalized medicine, where treatments are tailored to individual patients based on test results. Its approach differs from many peers by integrating drug discovery with diagnostic capabilities and by expanding its research through strategic acquisitions (like Genentech) to strengthen its biotechnology and R&D capabilities. The company’s goal is to improve patient outcomes and healthcare worldwide by delivering reliable medicines, accurate diagnostic tests, and data-driven care.

Company size
1-10
Company stage
IPO
Headquarters
Basel, Switzerland
Founded
1896

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