The Epidemiologist will work directly with the Chief Science Officer and be responsible for designing, executing, analyzing, and interpreting results of studies using state-of-the-art measures of human health. Studies cover a broad range of topics, including physical fitness, cognitive performance, causes of mortality (e.g., cancer, cardiovascular disease, dementia, diabetes), and molecular measures, so a broad and detailed knowledge base is helpful, but ability to learn independently is highly valued. Additional research projects focus on methodological questions related to technical accuracy, reproducibility, and clinical validity representing the full life cycle from research concept/finding to process testing. We collaborate with leading experts across multiple fields. Tele-work with monthly travel for in-person meetings. Work closely with interdisciplinary scientific team with expertise in genomics, epidemiology, bioinformatics, and machine learning.
Study design and analysis
Design and direct studies and analyses on a range of topics.
Ensure that studies are executed properly with regard to scientific validity.
Work with Data Science team on analytical objectives and interpretation.
Ensure data quality, including capture of all necessary data.
Knowledge of survey design and laboratory testing is desired.
Create summary reports/manuscripts (i.e., literature reviews as well as research papers for publication).
Identify and build collaborations with experts in the field, as they pertain to scientific goals of the company.
Conduct continuous literature search and evaluation of newly published research that is relevant to research goals.
Conference attendance, literature searches, and meetings with experts, as needed.
PhD in Epidemiology or related field
3+ years of experience in statistical programming
2+ years of secondary data analysis from major epidemiologic cohorts
Experience with study design and epidemiologic theory
Expertise in data cleaning and data curation of epidemiologic/clinical studies
Experience in applied statistics (e.g., regression, survival analysis, descriptive statistics)
Subject-specific expertise in one or more of the following: genetics, epigenetics, biomarker discovery/validation, and lifestyle behaviors (e.g., smoking, obesity, alcohol intake, diet, physical activity).
Data analysis programming skills in R or Python
Experience in survey/questionnaire design.
Expertise in laboratory testing and biomarkers of human health.
Understanding of Machine Learning/Data Mining algorithms and software tools (e.g., scikit-learn, caret)
Working knowledge of command line terminal (e.g., bash).
Working knowledge of git and GitHub for collaborative software development.
Working knowledge of the Python Data Science ecosystem (NumPy, SciPy, pandas, matplotlib, Jupyter Notebooks, etc.).
Base salary: up to $150,000 annually
Medical, Dental, Vision, Basic Life, Short-Term Disability, and Long-Term Disability insurance included.
Remote work allowed. In-person meetings with Science Team for minimum of 3-5 days quarterly. Travel expenses paid for by Company.
Continuing Education: Attendance of 1-2 research conferences per year, paid by Company.