Website Lenox Executive Search
6+ month extendable Contract role. High preference for candidate to work onsite at least one day per week in Bridgewater, NJ but also open to 100% remote candidates. Must have M.S in a Statistics, Mathematics, Computer Science or related field and at least 2 years experience in the pharmaceutical/biotech industry.
Lenox Executive Search is seeking an experienced Biomarker Statistics & Programming Specialist to fill an 6+ month extendable contractual role with a global pharmaceutical company in Bridgewater, NJ.. Must have strong knowledge of advanced statistical concepts and techniques in particular for high-dimensional data (cross-validation, multiple testing correction, feature selection).
REQUIREMENTS for the Biomarker Statistics & Programming Specialist:
- M.S in a Statistics, Mathematics, Computer Science or related field
- At least 2 years experience in the pharmaceutical/Biotech industry
- Strong knowledge of advanced statistical concepts and techniques in particular for high-dimensional data (cross-validation, multiple testing correction, feature selection)
- Expertise in omics data bioinformatics(RNAseq and single-cell RNAseq),proteomics and statistical analysis
- Experience in Machine Learning algorithms: penalized regression, SVM, random forest
- Strong knowledge of R
- Python would be a plus
- Demonstrated strong project management, interpersonal and communication skills (be able to understand discussions in a cross-functional setting in english)
RESPONSIBILITIES of the Biomarker Statistics & Programming Specialist:
- Perform tasks under the guidance of statistical lead on statistical analyses, modeling, reporting, analytic interpretations, and slide development analysis for biomarker data.
- Develop R modules and pipelines to standardize disease identification.
- Assist project lead in study design, power calculation, analysis and reporting for genomic datasets such as RNASeq, gene expression, Olink data (proteomics), FACS datasets.
- Apply relevant regression and machine learning tools on biomarker related questions such as patient stratification, diagnostic biomarkers, responder vs Non-responder status etc.
- Research and implement new ways to show data in graphs, dashboard and Shiny apps.