Research Statistician

Colorado School of Mines

Golden, Colorado, US
Hourly: $34.00 - $50.00 ph; benefits: flexible hea...
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Non-parametric and bayesian statistics
Large geochemical data analysis
Supervised learning techniques
** The Colorado School of Mines is seeking a Research Statistician to conduct statistical analysis on large geochemical datasets, focusing on causal inference and estimation. The ideal candidate will possess a Master's in Statistics and experience in advanced statistical methods, programming languages, and data analysis techniques relevant to mining and environmental studies. **

Job Summary

  • Colorado School of Mines is a top-ranked public university solving grand challenges related to the Earth, energy, and environment.
  • This position involves completing statistical analysis of large geochemical datasets and complex analysis for causal inference and estimation.
  • Mines offers a robust portfolio of benefits including flexible health and dental care, generous sick/vacation time, and a fully vested retirement plan on the first day of employment.

Matching Summary

Match Score: 75

** The Colorado School of Mines is seeking a Research Statistician to conduct statistical analysis on large geochemical datasets, focusing on causal inference and estimation. The ideal candidate will possess a Master's in Statistics and experience in advanced statistical methods, programming languages, and data analysis techniques relevant to mining and environmental studies. **

Salary

Hourly: $34.00 - $50.00 per hour; Benefits: Flexible health and dental care, generous sick/vacation time, 11% employee contribution to Defined Contribution Plan, 12% employer contribution to Defined Contribution Plan, tuition benefits, free RTD Ecopass, discount programs, free tickets for Mines Athletics home games, access to Recreation Center and Outdoor Rec Center, on-campus daycare center

Skills & Requirements

Must-have

  • non-parametric and Bayesian statistics
  • large geochemical data analysis
  • supervised learning techniques
  • SQL and LLMs
  • creation of Shiny apps
  • high proficiency in R, Python and C++
  • GitHub repository and code documentation
  • likelihood estimation
  • generalized linear models
  • asymptotic theory for estimation

Nice-to-have

  • research experience in mine waste data
  • transformational opportunity
  • mission-driven workplace
  • diverse and inclusive community

Key Requirements

  • MS in Statistics
  • Previous research experience in byproduct and mine waste critical mineral data analysis
  • Ability to support estimation methods with asymptotic theory

Work Rights

Not specified

Tailored Resume

Cover Letter