Data Scientist / Biostatistician – Clinical & Real World Data (Pharma / Biotech)

O projekcie: Data Scientist / Biostatistician – Clinical & Real World Data (Pharma / Biotech) We are looking for a Data Scientist or Biostatistician with experience working on clinical trial and/or real-world healthcare data. In this role, you will support data analysis and insight generation across clinical and real-world datasets, helping translate complex healthcare data into meaningful outputs for decision-making. You will work closely with cross-functional teams in a data-driven environment, contributing to projects related to clinical studies, real-world evidence (RWE), and healthcare data analysis. Wymagania: Experience - 3–5+ years of hands-on experience working with clinical trial and/or real-world data - Experience in pharma, biotech, CRO, or healthcare-related environments - Practical experience working with datasets such as EHR, claims, registries, or clinical trial data Technical skills - Experience with Python, R, SQL, or SAS - Strong data analysis and data manipulation skills - Understanding of statistical methods or data science approaches applied to healthcare data Nice to have - Familiarity with clinical data standards such as CDISC (SDTM, ADaM), OMOP, or HL7 - Experience in real-world evidence (RWE) or real-world data (RWD) projects - Experience working with large-scale healthcare datasets Profile we’re looking for - Strong analytical mindset and attention to data quality - Ability to work with complex, real-world datasets - Comfortable collaborating with both technical and non-technical stakeholders - Detail-oriented and able to work in regulated environments - Good communication skills in English Codzienne zadania: - Analyse clinical trial and/or real-world datasets (e.g. EHR, claims, registries) - Prepare, transform, and validate healthcare datasets for analysis and reporting - Apply statistical or data science methods to generate insights from clinical data - Work with structured and semi-structured healthcare data sources - Support development of data pipelines and analytical workflows - Collaborate with stakeholders to understand analytical needs and translate them into data solutions - Contribute to data standardisation and transformation processes (e.g. CDISC, OMOP – if applicable) - Ensure data quality, consistency, and compliance with industry standards