Biostatistical Scientist
Indexed description
Macks Life Science is a computational life-science company working at the intersection of bioinformatics, scientific computing, and applied research. We partner with researchers, healthcare organizations, and academic collaborators to turn complex biological and clinical data into rigorous, actionable insight. Alongside our core service work, we operate an R&D division building toward long-term, high-impact projects in the space.
We're looking for a Biostatistical Scientist to help us bring statistical rigor to research design, data analysis, and evidence generation across our projects, from clinical and genomic datasets to applied pharmacogenomics research.
The Role
As a Biostatistical Scientist, you will design and execute statistical analyses that support research integrity across our projects and collaborations. You'll work closely with researchers, data scientists, and domain experts to ensure every study, from a small pilot dataset to a larger applied research initiative, is built on sound statistical methodology.
Responsibilities
Design statistical analysis plans for research studies, including sample size and power calculations
Perform statistical analyses on clinical, genomic, and experimental datasets using appropriate methods (regression, survival analysis, Bayesian methods, multivariate analysis, etc.)
Collaborate with researchers and mentors to ensure studies are designed with statistical rigor from the outset
Interpret and communicate statistical findings clearly to both technical and non-technical stakeholders
Review and validate statistical methodology in research submitted for publication
Ensure compliance with relevant statistical and regulatory reporting standards (e.g., CONSORT, STROBE) where applicable
Collaborate cross-functionally with bioinformaticians, data engineers, and research fellows on ongoing projects
Stay current with emerging statistical methods and their application to genomics, pharmacogenomics, and clinical research
Contribute to internal training and mentorship for early-career researchers and fellows on statistical best practices
Requirements
Master's or PhD in Biostatistics, Statistics, Epidemiology, or a closely related quantitative field
Demonstrated experience applying statistical methods to biological, clinical, or genomic data
Proficiency in R, Python, or SAS for statistical computing
Strong understanding of experimental design, hypothesis testing, and common biases in biomedical research
Experience with statistical software and reproducible analysis workflows (R Markdown, Jupyter, version control)
Excellent written and verbal communication skills, with the ability to explain statistical concepts to non-statisticians
Meticulous attention to detail and strong documentation practices
Nice-to-Haves
Experience in pharmacogenomics, clinical trial biostatistics, or genomic epidemiology
Familiarity with regulatory statistical guidelines (FDA, EMA, ICH)
Prior experience mentoring or reviewing the statistical work of junior researchers
Publication record involving statistical methodology or applied biostatistics
What We Offer
The opportunity to shape statistical rigor and research methodology at an early-stage, computational life-science company from the ground up
Direct collaboration with our founding team and research fellows across multiple ongoing projects
Flexible, remote working structure
[Insert compensation structure once defined, e.g., base pay, contract terms, or equity discussion]
Macks Life Science is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Originally posted on Himalayas
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