Health, Applied & Quantitative Sciences Subject Matter Expert

DataForce by TransPerfect • Remote, United States, AMERICAS

1d • Remote

About The Position

DataForce by TransPerfect is seeking a recent PhD graduate or early-career researcher specializing in Health, Applied & Quantitative 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 Pharmacology, Toxicology, Biotechnology, Bioinformatics, Computational Biology, Neuroscience, and Immunology.

Requirements

• PhD completed or recently completed in Pharmacology, Toxicology, Biotechnology, Bioinformatics, Computational Biology, Neuroscience, Immunology, or a related Life Sciences field.
• 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 your area of specialization.
• 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 quality review.
• Experience using public scientific repositories and databases.
• Bioinformatics, computational biology, or data analysis experience.
• 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 health, applied, and quantitative 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.

What This Job Offers

• Career Level: Entry Level
• Education Level: Ph.D. or professional degree