Biostatistician / Data Scientist – Medical Analytics & Exploratory Data Sciences

Biostatistician / Data Scientist – Medical Analytics & Exploratory Data Sciences (Contract)

Contract role: 6+ months renewable

Location: Remote, US

Overview:

We are seeking a Biostatistician or Data Scientist to join our client’s Medical Analytics & Exploratory Data Sciences team. This group supports exploratory analyses including publications, reimbursement strategy, and European regulatory submissions, with a focus on patient-reported outcomes (PRO) and real-world evidence (RWE).

This role is ideal for candidates with either strong clinical trial SAS programming experience or advanced data science expertise applied within the life sciences industry.

Key Responsibilities:

• Conduct exploratory analyses to support publications, reimbursement, and regulatory filings (EU submissions)
• Work with clinical trial data, PRO, and RWE datasets
• Collaborate with cross-functional teams across clinical, regulatory, and medical affairs
• Contribute to study design, analysis plans, and interpretation of results
• Effectively communicate findings to both technical and non-technical stakeholders
• Manage multiple projects and timelines in a dynamic environment

Required Qualifications:

• Biostatistics --MS or PhD in Biostatistics, Statistics, or related field
• Strong SAS programming skills with clinical trial data
• Experience working with patient-level clinical datasets
• Understanding of regulatory and submission-driven analyses
• Prior pharma/biotech or CRO experience
• Strong project management and organizational skills and knowledge of clinical trial data
• Data Science –Advanced degree in a quantitative field (Statistics, Data Science, etc.)
• Expertise in machine learning and causal inference
• Proficiency in R programming (preferred)
• Industry experience in pharma/biotech strongly preferred
• Ability to translate complex analyses into actionable insights

*Must also have experience with:

• Oncology data
• Familiarity with real-world evidence (RWE) methodologies