ESSA Pharma - Clinical Data Scientist

Paid / Remote / Full-time

As a data scientist at ESSA Pharma, you will work closely with the organization’s lead
computational biologist to generate data-driven insights to advance our clinical and preclinical research goals while leveraging your skills in statistics and practical computational solutions. Your primary responsibilities will include analyzing multivariate clinical datasets utilizing parametric and non-parametric statistics, data wrangling, and building predictive models using data from various sources. The ideal candidate will be proficient in R (preferred) and/or Python and possess the ability to visualize data effectively.

Key Competencies and Qualifications:

Education: M.S. or Ph.D. in biology, data science, biostatistics, statistics, or a related field.

Data Science: Strong expertise in data science methodologies and techniques, including
data preprocessing, exploratory data analysis, and predictive modeling.

Non-Parametric Statistics: Proficiency in non-parametric statistical methods for analyzing
complex biological and clinical data.

Programming Languages: Proficiency in R (preferred) and/or Python and bash for data
analysis and modeling.

Biostatistics: Solid understanding of biostatistics, including study design, hypothesis
testing, and survival analysis.

Data Visualization: Proficiency in data visualization using ggplot2, plotly, or bokeh to
effectively communicate findings in markdown or shiny.

Data Wrangling and Cleaning: Strong skills in cleaning and preprocessing complex datasets
for analysis with proficiency in regular expressions.

Version control: Proficiency in collaborative coding projects and code maintenance with git
version control.

Communication Skills: Exceptional written and presentation skills to effectively
communicate results and insights to both technical and non-technical stakeholders.

Clinical Data Analysis: Experience in analyzing clinical data and contributing to the design
and execution of clinical research studies.

Power Analysis: Knowledge of power analysis techniques for sample size estimation in
experimental design.

Machine Learning (a plus): Experience in building supervised machine learning models for
classification or regression/prediction tasks.

Apply to this position

Interested candidates should submit their resume (pdf) and a cover letter detailing their relevant experience and qualifications to Brett Younginger at ESSA Pharma (

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