Professional Aide - Carter Lab
Quick Summary
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.
Master’s degree in statistics, data science, forestry, natural resources, or a related field Strong analytical and problem-solving skills Experience managing, cleaning,
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.
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
Requirements
~1 min readRequired 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
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.
Upload brief cover letter, resume/CV, and contact information for one professional reference.
Position will remain open until filled. Incomplete applications will not be considered.
STANDARD 8-5
for.msu.edu
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.
Advertised: Eastern Daylight Time
Applications close: Eastern Daylight Time
Location & Eligibility
Listing Details
- Posted
- July 30, 2026
- First seen
- July 30, 2026
- Last seen
- July 31, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 51%
- Scored at
- July 30, 2026
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