SC32P3- Information Scientist- Bioinformatician

CAS•Columbus, OH

9d•Onsite

About The Position

CAS is seeking a highly motivated and experienced Bioinformatician in the Life Sciences to join a cross-functional team supporting and enhancing the CAS Life Sciences data collection. The role works closely with scientists, data stewards, and technical teams to improve data quality by editing, changing, extracting, validating, and transforming scientific data into reliable, well-structured content. It also uses data analysis to measure and report progress, develops scalable analytical approaches, participates in unit-level projects, and supports related information databases. Additional work may include analyzing, curating, and harmonizing Life Sciences content, providing curation guidelines, and implementing process improvements. The position is based at CAS headquarters in Columbus, Ohio. Candidates must be authorized to work in the United States and must not require current or future employment visa sponsorship.

Requirements

Experience analyzing and interpreting large biological datasets.
Familiarity with public biological databases and ontologies, such as UniProt, ChEMBL, IMGT, and Gene Ontology.
Proficiency in SQL and working knowledge of Python or R for data analysis.
Experience evaluating and validating machine learning models.
Strong analytical and problem-solving skills, with close attention to detail.
Excellent written and verbal communication and collaboration skills.
Strong organizational and time-management skills, including the ability to manage multiple priorities and meet deadlines.
Ability to work independently and as part of a team.
Must be authorized to work in the United States and must not require work authorization sponsorship now or in the future.

Nice To Haves

An advanced degree in data science, life sciences (such as biology, biochemistry, chemistry, or pharmacology), omics (such as genomics, transcriptomics, proteomics, or metabolomics), computer science, or a related field; a bachelor's degree with extensive professional experience will be considered.
Experience with NoSQL or document databases such as MarkLogic, or with XML and JSON data.
Familiarity with schemas and data modeling.

Responsibilities

Analyze, validate, and audit Life Sciences datasets to identify errors, inconsistencies, duplicates, and gaps, and perform bulk corrections as needed.
Harmonize and standardize data using controlled vocabularies, ontologies, and internal data standards.
Query, extract, clean, and transform database data to support curation, reporting, and quality initiatives.
Integrate and verify data from internal and external sources, including public databases and partner data.
Perform quality control, normalization, and statistical analysis of high-throughput datasets.
Help define and track data quality metrics.
Evaluate and apply AI and LLM-based approaches, along with scripting, to automate harmonization, curation, and repetitive tasks.
Create clear reports, summaries, and visualizations for technical and non-technical stakeholders.
Collaborate with scientists, data stewards, and cross-functional teams to translate analytical needs into technical solutions, resolve data issues, and improve workflows.
Document processes, decisions, and data standards.