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Professional Aide - Carter Lab

Forestry 10002360

Support Staff

Professional Aide - Carter Lab

  • East Lansing, Michigan, United States
  • Forestry 10002360
  • Full Time/Part Time: Temporary
  • Remote Work: Remote-Friendly
  • Support Staff
  • Opening on: Jul 30 2026
  • Closing at: Aug 19 2026 - 17:00 EDT
  • 05
  • Pay Commensurate with Experience
  • College Of Agriculture And Nat Resources
  • 1150984
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Position Summary(Basic Job Function)

This is a temporary or an on-call position. Provides professional support. Responsibilities may include general business, science, medical, agricultural or other professional support functions. Term: Temps can work two (2) nine (9) month terms with a week break in service in between and at the end of the second term terminate for three (3) months or switch to an on-call. On-Call allowed to work 1039 hours in any twelve (12) month period.

Unit Position Summary

We are seeking a motivated and detail-oriented data analyst/statistician to support the Northern Hardwoods Resilience Project. This large-scale, multi-agency project, funded by the U.S. Forest Service, evaluates the current state of northern hardwood forests across the U.S. and Canada and examines how management practices and environmental factors influence their sustainability and resilience. The successful candidate will work closely with researchers and collaborators to prepare, summarize, and analyze large forest inventory and spatial datasets. This position is well suited for a person with strong quantitative skills who enjoys solving applied ecological and natural-resource questions.

Duration: 9 months beginning Oct 2026, with potential for extension.

Location: Department of Forestry, 480 Wilson Road, East Lansing. Remote work possible after the training period.

Work Schedule: Flexible self-managed schedule, 40 hours per week.

Primary duties:

  • Clean, organize, and process datasets for analysis
  • Conduct statistical and spatial analyses
  • Prepare maps, figures, tables, and summary statistics for presentations and manuscripts
  • Maintain clear documentation of data sources, analytical decisions, and code
  • Contribute to other project-related data analysis tasks as needed

Compensation: Pay starts at $30/hour depending on skills and experience

Desired Qualifications

Required qualifications:

  • Master’s degree in statistics, data science, forestry, natural resources, or a related field
  • Strong analytical and problem-solving skills
  • Experience managing, cleaning, and organizing large and complex datasets
  • Experience with statistical modeling, including mixed-effects, multivariate, or spatial analyses
  • Experience using R, JMP, ArcGIS, or comparable statistical and geospatial software
  • Ability to work independently and meet project deadlines
  • Strong organizational, technical writing, and communication skills
  • Attention to detail and commitment to producing well-documented, reproducible outputs

Preferred qualifications:

  • Experience working with FIA or similar forest inventory datasets
  • Experience identifying, evaluating, and integrating relevant publicly available datasets to support research questions and analyses
  • Experience with mapping or GIS
  • Experience contributing to scientific reports, presentations, or peer-reviewed manuscripts

Equal Employment Opportunity Statement

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status.

Required Application Materials

Upload brief cover letter, resume/CV, and contact information for one professional reference.

Special Instructions

Position will remain open until filled.  Incomplete applications will not be considered.

Work Hours

STANDARD 8-5

Website

for.msu.edu

Remote Work Statement

MSU strives to provide a flexible work environment and this position has been designated as remote-friendly. Remote-friendly means some or all of the duties can be performed remotely as mutually agreed upon.

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