Job Title: Data Analyst
Type: Full-time, Independent Contractor
Location: Remote, Latin America (LATAM)
Work Hours: 9:00 AM – 5:00 PM US Eastern Time
Our client is a software, data, and research company partnering with health & wellness brands, universities, and government agencies.
We’ve built a remote study management platform that engages participants to collect real-world data on product use and performance over weeks or months.
Our team transforms that data into in-depth reports highlighting product efficacy, statistically significant outcomes, and interaction models.
We are seeking a LATAM-based Data Analyst with deep experience in R, fixed effects models, and longitudinal data analysis.
This role will work under the Lead Statistician to run advanced analyses, prepare polished data reports, and contribute to evidence-based insights for clients.
Collaborate with the Lead Statistician on advanced data cleaning, validation, and exploratory analysis with longitudinal datasets.
Run fixed effects models and longitudinal / generalized mixed-effects models (GLMMs) as core outputs for interpreting product impacts and moderating effects.
Implement basic statistical tests and regression models as needed.
Create visual displays of raw longitudinal data (e.g., boxplots, bar charts) and statistical model output (e.g., predicted regression lines, marginal effects plots).
Generate reproducible tables, visualizations, and narrative summaries for client data reports using Rmarkdown/Rquarto.
Explore and integrate AI/ML tools (e.g., ML libraries, LLMs) to improve analysis workflows.
Document analysis pipelines and maintain reproducible, well-structured code.
Communicate findings clearly to both technical and non-technical stakeholders.
Based in Latin America (LATAM).
Master’s or PhD in Statistics, Data Science, Biostatistics, or related field.
R as the primary language (must-have).
Hands-on experience running fixed effects models.
Strong background in longitudinal data analysis (e.g., linear mixed models, multilevel modeling).
5+ years of experience creating data reports or research summaries.
Prior use of Rmarkdown/Rquarto for reproducible reporting.
Strong visualization skills for both raw and modeled data.
Excellent written and verbal communication in English.
Detail-oriented, self-starter, and comfortable in a fast-paced environment.
Preferred:
Familiarity with Python for supplementary analysis.
Experience integrating AI/ML tools into statistical workflows.
Prior work with health, wellness, or research-driven datasets.