Bee Ecotoxicological Data Science Intern

Job Description

The U.S. Geological Survey is recruiting a Student Services Contractor (SSC) to support a quantitative risk-modeling project titled “Probabilistic Extrapolation Factors for Bee Risk Assessment.” This project develops probabilistic, data-derived distributions for extrapolation factors used in pollinator risk assessments and combines them via Monte Carlo simulation to produce Composite Extrapolation Factors (CEFs). The work directly supports US-EPA, EFSA, OECD methodological guidelines and the U.S. Fish and Wildlife Service Pollinator Action Plan.

You will help advance transparent, reproducible risk science through statistical modeling, simulation, and literature-based data synthesis. Work will be carried out primarily in R, with expectations for clean, documented, reproducible code suitable for public release.

How to Apply 

Submit the following materials to wthogmartin@usgs.gov:

· Brief cover letter describing your interest in the position and ecological/environmental work and how this position could help your career

· Résumé (2-page limit) including three references

· Unofficial transcript showing degree earned and, if applicable, any academic distinctions

· Non-US citizens must describe their visa status (the U.S. government cannot sponsor work visa status)

· Applications will be reviewed as they are received.

Responsibilities

Responsibilities include:

· Collaborating with USGS researchers and U.S. Fish and Wildlife Service ecotoxicologists to

· Perform literature review and data inventory development

· Implement Monte Carlo simulations and generate summary statistics (mean, SD, median, P5, P50, P90, P95)

· Fit statistical distributions, document assumptions, and conduct diagnostics

· Create and maintain R code with QA/QC, reproducibility, and Git version control

· Prepare reports, metadata, figures, and narrative documentation

· Support reproducible science workflows and update datasets as the project evolves

Typical project tasks may include: 

• Conducting literature reviews and building a structured data inventory (species, caste, exposure route/duration, endpoint)

• Conducting Monte Carlo simulations of extrapolation subfactors (interspecies, intraspecies, exposure duration, route, lifestage, effect severity) 

• Fitting and diagnosing statistical distributions (lognormal, gamma, triangular, Beta-PERT) 

• Creating sensitivity and uncertainty analyses 

• Developing a governed project repository and preparing code for public release (README, metadata, unit tests, reproducible seeds) 

• Writing narrative descriptions of modeling methods and alignment with regulatory frameworks

Milestones include data inventory and assumptions, distribution fitting and diagnostics, simulation engine development, sensitivity analysis, and preparation of a final report and code archive.

Location

Upper Midwest Environmental Sciences Center, La Crosse, Wisconsin 54601 

OR

Oregon Coast National Wildlife Refuge Complex, Newport, Oregon 97365 (Office-like setting; remote options may be available with approval.)

When

Start date: As soon as possible, likely June 2026 (pending background check) Duration: Up to two years; part-time options during the school year available

Eligibility

Students are eligible if they are enrolled in a degree program or have graduated but received a college/university degree less than 12 months ago and are at least 18 years of age. Non-US citizens may be eligible to participate, depending on their immigration status and the applicable regulations of the U.S. Citizenship and Immigration Service. USGS employees, their spouses, and their children are not eligible to participate in this program.

Qualifications

Minimum: 

• ≥1 year of graduate-level coursework in quantitative ecology, applied statistics, biometrics, quantitative wildlife/fisheries science, or applied mathematics 

• Knowledge of applied statistical modeling and risk modeling 

• Proficiency with R (distribution fitting, diagnostics, visualization, sensitivity analysis) 

• Ability to perform literature-based parameter extraction 

• Ability to learn or use Git for reproducible version control

Preferred:

· Understanding of uncertainty propagation; familiarity with Monte Carlo simulation

· Experience with copulas for dependence modeling

· Prior work in population modeling, toxicity modeling, or environmental risk assessment

· Experience conducting simulation studies comparing risk-scenario outputs

Hourly Rate of Pay

$38.52 (GS Scale Equivalent GS-11; MA/MS-level)

Additional Information

• This is an independent-contractor position. Students are paid for each hour worked. Students will be working as independent contractors and do not receive a premium rate for work beyond 8 hours/day or 40 hours/week.

• Sick leave accrues at 1 hour per 30 hours worked; no holiday or personal leave • Pay rates reflect self-employment tax considerations (i.e., cost of self-employment taxes for social security and Medicare). • Work may require travel to scientific meetings; USGS covers transportation, meals, and lodging per federal rules