Data Scienist

At Madiff, we connect top IT talent with cutting-edge companies through remote Agile teams and nearshore outsourcing. With operations in Poland, Portugal, France, and the UK, we specialize in AI, DevOps, and Cybersecurity – supporting industries like Telecom, Banking, and Hi-Tech.

Are you excited about the future of Generative AI and want to shape how enterprises apply LLMs and ML at scale?

We’re looking for a Data Scientist with Generative AI expertise to support the AI transformation program of a leading global consulting firm.

What you will do:

• Design, fine-tune and optimize LLMs and GenAI pipelines using Python, PyTorch, TensorFlow, MLflow, and LangChain

• Build and scale RAG systems and advanced prompting (chain-of-thought, function-calling)

• Develop and deploy predictive models (classification, time-series forecasting) in CI/CD environments with Docker and MLflow

• Implement robust AI governance frameworks – including compliance, monitoring, and ethical guidelines

• Lead internal adoption workshops, mentor junior team members, and drive business alignment

• Collaborate on data ingestion, feature engineering, model evaluation, and feedback loops

  
  

What we are looking for:

• Min. 3 years as a Data Scientist, with practical experience in GenAI and ML workflows

• Excellent Python skills with PyTorch, TensorFlow, Scikit-learn, Pandas, and NumPy

• Experience with cloud platforms (Azure, Databricks) and MLOps tools like MLflow, CI/CD

• Proven success in LLM fine-tuning, prompt engineering, and RAG architecture

• Solid knowledge of forecasting and predictive modeling

• Strong communication, stakeholder engagement, and mentoring abilities

• Fluent English - spoken and written

Nice to Have:

• Familiarity with Dataiku, Apache Spark, GraphQL, or React Native

• Domain experience in healthcare or fintech

• Advanced degree (MSc/PhD) in Data Science, AI, or related field

What we offer:

• Fully remote work set-up

• Comprehensive medical care

• Long-term opportunity to shape GenAI adoption in highly regulated, high-impact industries