Scientific Data & Systems Specialist
Job Title: Scientific Data & Systems Specialist Location: Remote Duration: Long Term Position Overview We are seeking a detail-oriented and scientifically-minded Scientific Data & Systems Specialist to join the Computational Sciences Center of Excellence (CS CoE) organization at Research and Early Development (gRED). This role is the critical bridge between experimental biology and computational engineering. You will enable and accelerate drug discovery by ensuring that high-dimensional data is properly manicured, harmonized, and integrated into our large-molecule registration and request systems.
Key Responsibilities
Data Curation & Integrity: Manicure and update scientific data stored in internal systems, including large molecule registration and LIMS, to ensure accuracy and reproducibility. Database Management: Utilize SQL to design queries and retrieve data from relational databases such as Oracle, MySQL, or Postgres. Workflow Automation: Automate and parallelize repetitive data-processing tasks using programming languages like Python, R, Bash, or Perl to improve operational efficiency. Bioinformatics Support: Apply sequence alignment tools (e.g., BLAST, CLUSTALW) and reference publicly available DNA/protein databases (e.g., UniProt, Genbank, Ensembl) to validate internal data. Quality Assurance: Write unit and functional tests to ensure the quality and stability of data-processing code. Cross-Functional Communication: Effectively convey complex data analysis results to diverse audiences, including scientists, product owners, and software developers, through platforms like Jupyter or R Notebooks. Qualifications & Requirements Education & Experience Education: B.S., Master’s, or PhD in Biology, Bioinformatics, Molecular Biology, Computer Science, or a related quantitative field. Experience: 1–3 years of relevant experience in a scientific or industry environment, particularly within large-molecule drug development. Technical Skills Data Systems: Familiarity with bioinformatics tools and packages (e.g., Biopython, Bioconductor, Bioperl). Programming: Strong proficiency in SQL and at least one scripting language (Python, R, or Bash) for data manipulation. Public Resources: Experience using standard biological databases (UniProt, Ensembl) and sequence analysis software. --