Bioinformatics Scientist (Drug Discovery & AI Training)

About Us

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

Role Overview

We are looking for an experienced Bioinformatics Scientist to support a scientific project focused on improving how advanced AI systems understand biological, chemical, and drug-discovery data.

You will analyse and validate complex datasets, review AI-generated scientific content, and contribute expert insights across bioinformatics, medicinal chemistry, cheminformatics, and molecular analysis. Previous AI experience is not required.

CONTRACT: Freelance contractor, paid per completed task

COMMITMENT: Flexible, based on available tasks and project demand

LOCATIONS: Fully remote - GLOBAL

PROCESS: Application review, technical assessment, and onboarding

HOURLY RATE: $90-$120/h

Responsibilities

• Analyse biological, chemical, and clinical datasets relevant to drug discovery.
• Curate, annotate, and validate scientific data.
• Evaluate AI-generated outputs for accuracy, relevance, and reliability.
• Interpret findings from omics, cheminformatics, and molecular datasets.
• Develop scientific content and realistic medicinal chemistry scenarios.
• Provide input on experimental design and data interpretation.
• Identify data-quality issues, inconsistencies, and unsupported conclusions.
• Deliver structured feedback and recommendations to improve AI outputs.

Requirements

• Advanced degree in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related field.
• Experience analysing large-scale biological, omics, or cheminformatics datasets.
• Strong knowledge of medicinal chemistry, structure–activity relationships, or drug-design principles.
• Proficiency with bioinformatics or cheminformatics tools and programming languages such as Python, R, RDKit, or KNIME.
• Experience interpreting scientific literature and communicating technical findings clearly.