Ecological, Evolutionary & Environmental Sciences Subject Matter Expert

DataForce by TransPerfectRemote, United States, AMERICAS
Remote

About The Position

DataForce by TransPerfect is seeking a recent PhD graduate or early-career researcher specializing in Ecological, Evolutionary & Environmental Sciences to support a large-scale research and data validation project. The ideal candidate will have a strong academic research background and hands-on experience working with scientific datasets, publications, and research databases within their area of expertise. Relevant backgrounds include Ecology, Evolutionary Biology, Marine Biology, and Environmental Science.

Requirements

  • PhD completed or recently completed in Ecology, Evolutionary Biology, Marine Biology, Environmental Science, or a related Life Sciences field.
  • Up to 5 years of professional, academic, or postdoctoral experience.
  • Demonstrated research experience through publications, thesis work, laboratory research, or postdoctoral projects.
  • Experience working with scientific datasets and research databases.
  • Familiarity with datasets, repositories, and data sources relevant to ecological, evolutionary, and environmental sciences.
  • Strong analytical and problem-solving skills.
  • Exceptional attention to detail.
  • Ability to identify errors, inconsistencies, and quality issues in scientific data.
  • Strong written and verbal communication skills.

Nice To Haves

  • Experience with data curation or data review.
  • Experience using public scientific repositories and databases.
  • Experience with data analysis or computational biology.
  • Familiarity with AI-driven research tools.
  • Experience reviewing scientific literature and validating scientific content.

Responsibilities

  • Review scientific content, publications, and research data within your area of expertise.
  • Navigate and utilize leading research datasets, repositories, and databases relevant to ecological, evolutionary, and environmental sciences.
  • Curate, validate, and organize scientific data.
  • Identify incorrect, inconsistent, incomplete, or potentially misleading scientific information.
  • Verify scientific claims against published research and established datasets.
  • Assess data quality, relevance, and reliability.
  • Support data annotation, classification, and quality assurance activities.
  • Apply critical scientific thinking to evaluate research outputs and data sources.
  • Clearly communicate findings, issues, and recommendations.
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