Quantitative Analyst
What this job does:
Designs and implements analytical frameworks to extract strategic insights from complex biological, clinical, or health data - such as real-world evidence, electronic health records, genomic data, or claims data. Day-to-day involves formulating research questions, building statistical or machine learning models, and synthesizing quantitative findings into strategic recommendations that inform drug development, market access, clinical operations, or health outcomes research.
This job is similar to these lab/research tasks:
Designing experiments and selecting statistical approaches, interpreting complex datasets, defending analytical choices to skeptical reviewers, synthesizing findings into a clear narrative with appropriate uncertainty
Typical starting salary range
$130k to $200k
Salary estimate represented as 25th to 75th percentile. Gathered from recent job postings, Glassdoor.com, and Salary.com
Daily task breakdown
- Building and executing quantitative models on health and life sciences data: statistical analyses, ML/AI, predictive models (30%)
- Framing complex biological and clinical questions as quantitative analyses: study design, method selection, analytical plans (25%)
- Synthesizing quantitative findings into strategic insights: reports, dashboards, presentations (20%)
- Data wrangling, curation, and quality assessment; working with engineering on data pipelines (15%)
- Other: literature review, cross-functional collaboration, mentoring, peer review (10%)
Skills you'll use in this job:
Advanced statistical methods (regression, survival analysis, Bayesian methods, causal inference); Python and R (required); SQL; machine learning and AI applied to biological or health data; deep understanding of clinical and health data types (EHR, claims, genomic, trial data); epidemiological study design knowledge; scientific domain expertise in biology, pharmacology, or medicine; data visualization (ggplot, matplotlib, Tableau); communication of quantitative results to non-technical stakeholders; healthcare ontologies (ICD, CPT, SNOMED); cloud computing (AWS, GCP); critical data quality evaluation
Talk about these PhD skills in your resume and interview:
Talk about designing experiments, selecting statistical approaches, and interpreting complex datasets - the exact workflow of framing a question, choosing a method, executing the analysis, and synthesizing findings into a narrative. Talk about defending analytical choices to skeptical reviewers, which mirrors presenting quantitative models to investment committees.
Alternative job titles to search:
Quantitative Researcher - Healthcare; Quantitative Scientist; Health Data Scientist; Biostatistician (industry); Real-World Evidence Analyst; RWE Scientist; Outcomes Research Analyst; Computational Scientist - Health; HEOR Analyst; Applied Scientist - Healthcare
*Note:
-Job titles are inconsistent between companies. Try various keywords.
-PhDs tend to undershoot seniority level. Target higher than you think.
