Job Title
LTE Wildlife Research Analyst (Madison)
Job ID
18824
Location
Madison
Agency
Natural Resources
Full/Part Time
 
Regular/Temporary
Temporary

Introduction

 

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We are dedicated to working with Wisconsinites while preserving and enhancing the natural resources of Wisconsin. In partnership with individuals and organizations; DNR staff manage fish, wildlife, forests, parks, air and water resources while promoting a healthy, sustainable environment and a full range of outdoor opportunities.

The Wisconsin DNR is hiring an LTE (Limited Term Employee) – Wildlife Research Analyst, in Madison, WI.

This recruitment may be used to fill future similar vacancies. 

To see all opportunities currently available at DNR, follow this link: DNR (wisc.jobs).

Position Summary

 

The Office of Applied Science within the Wisconsin Department of Natural Resources (DNR) is hiring a Wildlife Research Analyst to join the Snapshot Wisconsin Decision Support Research Program. This program uses the 100+ million trail camera photos collected by the Snapshot Wisconsin program to conduct applied research and develop annual products that support wildlife decision making. The position will support applied research and development of population metrics from Snapshot Wisconsin trail camera data to inform management of deer, turkeys, and other Wisconsin wildlife species. This person will process and analyze Snapshot Wisconsin detection data working towards finalizing years of data. This person is expected to write custom SQL queries, write and annotate R code, fill data requests, and implement automated processing of research products whenever possible. This person will be responsible for conducting data-based research projects, running statistical analyses and models, and assessing model results. The position will be based out of Madison, WI.

 

40% Processing, documenting and finalizing trail camera detection data

      Pull and process Snapshot Wisconsin trail camera data from an Oracle database and using custom SQL queries and R functions

      Fill data requests that come in from volunteers, students, researchers, and DNR employees

      Contribute to user acceptance testing of Oracle database changes that fix bugs or add features

      Contribute to custom R packages for data analysis, especially adding documentation and new functions

      Assess data quality and identify inconsistencies in data that require further assessment

      Identify and implement solutions to finalize annual Snapshot Wisconsin datasets 

 

30% Statistical analysis and model development

      Assess patterns in data to separate noise (e.g., sampling issues, classification differences, detection differences) from abundance trends

      Analyze trail camera data using a range of statistics and models that include covariates 

      Analyze trail camera data using models that include covariates and assess model fit and predictions

      Visualize statistics and model predictions spatially and temporally

 

20% Automation development for annual wildlife research products

      Critique existing workflows to identify steps that could be improved with automation

      Develop and implement new procedures that increase automation and reduce manual processing

      Fully document processes to improve usability annually and for similar applications

 

10% Other duties as assigned

Salary Information

 

This position pays $27.68 per hour and is in the Research Analyst Senior classification in pay schedule and range 08-03. Compensation will be set in accordance with the State Compensation Plan. 

Job Details

 

This is a Limited Term Employment (LTE) position and will not automatically lead to permanent state employment or be entitled to the same benefits as permanent employees. 

More about LTE positions:

1) Offer a great opportunity to gain experience and learn about careers at the WI Department of Natural Resources.

2) Provide opportunities for individuals to enhance their resumes with skills learned on the job. 

3) May accommodate flexibility for part-time or full-time work hours and seasonal schedules. Work schedules are dependent on business needs. 

4) Allow individuals to hold multiple LTE appointments concurrently. If both LTE positions are at the same agency, the positions must be bona fide different positions. Each individual LTE position allows for maximum of 1039 hours in a twelve-month period.

Special Requirements:

1) Background Checks: The Department of Natural Resources conducts criminal background checks on final applicants prior to a job offer. Please note that a criminal charge or conviction on your record will not necessarily disqualify you from state employment. In compliance with the Wisconsin Fair Employment Act, the DNR does not discriminate on the basis of arrest or conviction record.

2) Eligible to work in U.S.: Applicants must be legally authorized to work in the United States at the time of hire. The Department of Natural Resources does not sponsor work visas at the time of hire or anytime during employment. All persons hired will be required to verify identity and eligibility to work in the United States and complete the required Employment Eligibility I-9 form upon hire.

Equal Opportunity Employer: The DNR is an equal opportunity employer that promotes and values diversity. We do not discriminate on the basis of race, ethnicity, religion, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability.

Qualifications

 

In addition to the required qualifications below, the selected candidate must be eligible to drive a state vehicle and meet the following criteria:

  • Have a valid driver’s license
  • Be at least 18 years of age
  • Have a minimum of two years licensed driving experience
  • Have not had three (3) or more moving violations and/or at-fault accidents in the past two (2) years
  • Have no OWI/DUI violations within the past year

 

Required qualifications:

 

  • Demonstrated proficiency with pulling and querying data from relational databases (e.g., SQL) 
  • Demonstrated proficiency with data cleaning, data wrangling and documentation using R or similar (e.g., tidyverse, RMarkdown)
  • Demonstrated proficiency with data analysis coding languages (e.g., R and Python)
  • Demonstrated proficiency in statistical analysis and modeling of big data (e.g., generalized additive mixed models)
  • Demonstrated proficiency with automation development
  • Demonstrated proficiency in research data collaborations

 

Preferred Qualifications:

 

  • Master’s degree or higher in data science, statistics, quantitative ecology, biology or a related field
  • Experience developing R packages
  • Experience with Python
  • Experience with version control in GitHub, or similar
  • Experience with computer programming and machine learning
  • Experience with trail camera research projects and trail camera data

How To Apply

 

Click the “Apply for Job” button and follow the directions. You will be able to save your application as many times as needed and make edits up until the point you submit your application. Once you submit your application, you will not be able to make any updates to the application or any materials submitted.

Please note that the Wiscjobs system will time you out after 30 minutes of activity, so be sure to save your work often to avoid having to re-start the application process.

For any position-related questions, please feel free to contact Jennifer.Stenglein@wisconsin.gov.

For technical questions and troubleshooting related to the Wisc.Jobs site, please visit Commonly Asked Questions. Keep in mind that technical assistance is only available Monday through Friday 7:45 am – 4:30 pm. 

Your resume and letter of qualifications are very important parts of your application and are used during our evaluation process to determine your qualifications as they relate to the job. For instructions on developing your resume and letter of qualifications and what should be included in these materials, click here.

Deadline to Apply

 

Applications must be received by 11:59pm, Central Time, on September 29th, 2025 in order to be considered.