Entry-Level Environmental Statistician

AECOM•Novi, MI
•Onsite

About The Position

AECOM is seeking an entry-level Environmental Statistician to support its environmental remediation and consulting teams in the Novi or Grand Rapids, Michigan offices. This early-career position is suited to someone with a strong quantitative background who is interested in applying statistical methods to environmental data and real-world environmental challenges. The position is expected to begin ASAP. The successful candidate will work with experienced scientists and technical professionals to organize, analyze, visualize, and interpret environmental datasets. The role supports project teams in evaluating environmental data and preparing technically sound analyses for reports, presentations, and client deliverables. The employee will support multiple environmental projects while meeting established schedules and quality requirements. This position requires U.S. citizenship. Relocation assistance is not available. Newly hired employees must attend in-person Day 1 onboarding at an AECOM office location as a condition of employment.

Requirements

  • Bachelor's degree in Statistics, Applied Mathematics, Data Science, Environmental Science, Environmental Engineering, or a closely related quantitative discipline.
  • U.S. citizenship is required due to the nature of the work.
  • Strong quantitative, analytical, and problem-solving skills.
  • Ability to communicate analytical results clearly in writing and verbally.
  • Ability to work effectively as part of multidisciplinary project teams.

Nice To Haves

  • Master's degree or graduate coursework in Statistics, Biostatistics, Applied Mathematics, Data Science, Environmental Science, or a related discipline.
  • Coursework or experience in environmental statistics, spatial statistics or geostatistics, sampling design, regression, multivariate analysis, or time-series analysis.
  • Familiarity with analytical tools such as R, Python, SAS, MATLAB, or similar statistical software.
  • Proficiency with Microsoft Excel and other Microsoft Office applications.
  • Familiarity with GIS or spatial datasets.
  • Experience working with environmental, laboratory, groundwater, soil, sediment, surface-water, or other scientific datasets.
  • Previous internship, research, or academic project experience involving statistical analysis of real-world data.

Responsibilities

  • Compile, organize, review, and analyze environmental datasets from investigation, monitoring, and remediation projects.
  • Perform statistical analyses under the direction of senior statistical and technical staff.
  • Assist with exploratory data analysis, data visualization, trend evaluation, and interpretation of results, including developing tables, figures, charts, and other visualizations for technical reports and presentations.
  • Support statistical evaluations of environmental sampling and monitoring data.
  • Develop dashboards and automate reporting.
  • Assist with quality control and validation of datasets before statistical analysis.
  • Use statistical and analytical software such as R, Python, Excel, or similar tools to manage and analyze data.
  • Help project teams interpret analytical results and communicate findings clearly to technical and nontechnical audiences.
  • Collaborate with environmental statisticians, scientists, engineers, geologists, GIS professionals, and other project team members.
  • Document analytical methods, assumptions, results, and supporting information clearly and reproducibly.
  • Support multiple environmental projects while meeting established schedules and quality requirements.

Benefits

  • Medical, dental, vision, life, AD&D, and disability benefits
  • Paid time off and leaves of absence
  • Voluntary benefits and perks
  • Flexible work options
  • Well-being resources and employee assistance program
  • Business travel insurance
  • Service recognition awards
  • Retirement savings plan
  • Employee stock purchase plan
  • Comprehensive benefits, depending on employment status
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