Senior Data Scientist – LLM / Clinical NLP
V
VectenHealthcare data
Remote PolandContractSenior
Salary30,000 - 38,000 PLN per month
Apply NowOpens the employer's application page
Job Details
- Languages
- Pl C1, en C1; Fluent English
- Experience
- Around 5 years of hands-on data science or ML work
- Required Skills
- PythonSQLLLM
Requirements
- Master's degree or PhD in a quantitative field such as computer science, machine learning, data science, or biostatistics.
- Around 5 years of hands-on data science or ML work, including taking models to production on messy real-world data.
- Hands-on NLP experience with transformer encoders, including fine-tuning BERT or RoBERTa-family models and biomedical or clinical variants such as BioBERT or ClinicalBERT.
- Experience with NER, classification, or relation extraction, typically using Hugging Face Transformers.
- Hands-on generative LLM experience with prompt design, structured outputs, fine-tuning such as LoRA / PEFT, and RAG.
- Experience evaluating LLM outputs at scale using gold sets, error analysis, or LLM-as-judge.
- A rigorous approach to evaluating whether models are correct, not merely plausible.
- Strong Python and SQL.
- Use AI tools such as Claude and Cursor as a core part of delivery.
- Fluent English and confidence presenting to cross-functional and non-technical stakeholders.
- Preferred: experience with EHR data or clinical notes and familiarity with ICD, CPT, or RxNorm.
- Nice to have: PySpark, Databricks, MLflow, AWS, Amazon SageMaker, R, medical imaging data, real-world evidence studies, peer-reviewed publications, or TypeScript.
Responsibilities
- Build and improve LLM- and transformer-based pipelines for extracting structured data from clinical notes, including named entity recognition, text classification, and relation extraction.
- Evaluate models using gold-standard datasets, error analysis, and metrics trusted by clinicians and researchers.
- Fine-tune, deploy, and monitor models in production.
- Work with Medical and Product teams to turn clinical questions into concrete data and model requirements.
- Present results and trade-offs clearly to technical and non-technical audiences.
View Full Description & ApplyYou'll be redirected to the employer's site
