This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
Research Position: Statistical Software Development for the Illicit Drug Landscape
Position Overview
This position supports an ongoing, interdisciplinary effort within the National Institute of Standards and Technology (NIST) to gain insights from data collected as part of the Rapid Drug Analysis and Research (RaDAR) program. NIST collaborates with public health and public safety stakeholders across the U.S. to analyze real-time data regarding the chemical makeup of illicit drugs. Because this landscape is opaque and rapidly evolving, the team is developing novel statistical and computational tools to model usage patterns, detect emerging trends, and surface analytical insights for stakeholders.
The successful candidate will focus primarily on software development for data science and statistical applications, with an emphasis on building and maintaining an interactive R Shiny web application (or similar tooling) that enables analysts and external stakeholders to explore and answer their own questions about drug compound data. The role also includes contributing to the implementation of statistical methods for projects that arise, such as detecting previously unobserved compounds and emerging trends. This is well-suited to a master's-level scientist who enjoys translating statistical and scientific requirements into robust, usable software.
Candidates must be eligible to obtain a Department of Commerce background check for facility access.
Key Responsibilities
- Dashboard Development: Design, build, and maintain a production-quality R Shiny application that allows non-statistical users to interactively query, visualize, and interpret high-dimensional drug compound data. Translate stakeholder analysis questions into reusable interface components and workflows.
- Software Engineering Practices: Develop modular, well-documented, and maintainable R code. Implement reactive data pipelines that remain performant on large, frequently updated datasets.
- Method Implementation: Collaborate with statisticians to implement and operationalize analysis methods—including approaches for detecting emerging or previously unobserved compounds—as tested, reusable functions and dashboard features.
- Data Analysis & Visualization: Conduct exploratory data analysis, data provenance and quality evaluation, and create publication- and presentation-quality visualizations (e.g., ggplot2, plotly) to support both the dashboard and team research.
- Collaboration & Communication: Work closely with statisticians, chemists, and public health stakeholders to gather requirements, iterate on tools, and present software capabilities and analytical findings to technical and non-technical audiences.
Qualifications
- Master's degree in Statistics, Biostatistics, Data Science, Computer Science, or a related quantitative field.
- Strong programming proficiency in R, including demonstrated experience developing R Shiny applications.
- Experience with software development best practices: version control (Git), modular code organization, documentation, and testing.
- Working knowledge of statistical concepts sufficient to collaborate effectively with statisticians and to implement analytical methods correctly.
- Proficiency in data manipulation and visualization in R (e.g., tidyverse).
- Familiarity with reactive programming patterns and performance optimization for interactive applications is desirable.
- Exposure to spatial, temporal, or spatio-temporal data, or to anomaly/novelty detection methods is a plus.
- Experience or interest in applying analytical tools to public health, chemistry, forensic science, or epidemiological data.
- Experience communicating technical ideas and tools to non-technical users.
The university is an Equal Employment Opportunity employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.