Scientific Knowledge Engineer

LanceSoft Inc; Durham (NC); Remote; USD 90,000 - 130,000; Full time

Job summary

A leading company seeks a Scientific Knowledge Engineer to focus on data harmonization and ontological standards in a fully remote capacity. Ideal candidates should possess a Bachelor's degree and 5+ years of relevant experience in data analysis, semantic technology, and biological research. This 6-month role will involve defining data schemas, ensuring data quality, and collaborating closely with product teams to enhance drug and vaccine discovery through effective data integration.

Qualifications

• 5+ years of experience in scientific knowledge engineering and data harmonization.
• Specialized knowledge of scientific ontology and metadata standards.
• Experience with bioinformatics is a plus.

Responsibilities

• Define schemas and data models for scientific information.
• Ensure quality control of data mapping specifications.
• Collaborate with teams to integrate large-scale biology data.

Skills

Data Analysis

Semantic technology

Data harmonization

Meta data experience

Attention to detail

Spreadsheet skills

SQL

Education

Bachelor’s degree

Tools

Jupyter Notebooks

NextFlow

GitHub

Protégé

GraphQL

Job description

Job Title: Scientific Knowledge Engineer/Data harmonization
Location: Durham, NC 12460-0070
Duration: 07/01/2025 to 12/31/2025 (6 Months0
Work Schedule: Monday-Friday – 9-5pm

Fully Remote – No onsite requirement – Candidates will need to be in the following cities - Seattle, Boston, Philadelphia, San Francisco

• Definition of schemas and data models of scientific information required for the creation of value adding data products.
• This includes accountability for the quality control and mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling.
• Accountable for the quality control (through validation and verification) of mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling – e.g., models, schemas, controlled vocab.
• Working with Product managers/engineers confidently convert business need into defined deliverable business requirements to enable the integration of large-scale biology data to predict, model, and stabilize therapeutically relevant protein complex and antigen conformations for drug and vaccine discovery.
• Collaborate with external groups to align CLIENT data standards with industry/ academic ontologies ensuring that data standards are defined with usage/analytics in mind.
• They may also provide data source profiling and advisory consultancy to R&D outside of Onyx.
• Support effective ingestion of data by CLIENT through understanding the entry requirements required by platform engineering teams and ensuring that the “barrier for entry” is met e.g. Scientific information has the appropriate metadata to be indexed, structured, integrated and standardized as needed.
• This may require articulation of CLIENT engineering standards and metadata information needs to third parties to ensure efficient and automate ingestion at scale.
• Provides bespoke subject matter expertise for R&D data to translate deep science into data for actionable insights

Candidate Requirements:

• Must-have Skills experience
• What type of individual excels in your environment and why?
• Non-essential requirements that would give the candidate an edge.
• Degrees or certifications required
• Would you consider candidates from other industry background?
• Bachelor’s degree
• Specialized knowledge of scientific ontology and metadata standards
• Semantic technology experience
• Data harmonization
• Meta data experience

Job 1: Skills for data harmonization
Experience with
• Data Analysis by Jupyter Notebooks, Python
• NextFlow pipeline
• Bioinformatics/data science
• GEO, single cell data
• Code versioning (GitHub)
• LinkML
• Ontology usage and basic understanding, knowledge of common biomedical ontologies
• Single-cell technologies
• Attention to detail
• Spreadsheet wizardry
• Regular expressions
• SQL
• anndata format (nice-to-have)
• Google cloud (nice-to-have)
• Bioinformatics/data science --> yes, some experience in this is helpful, at least knowing what the basic steps in an NGS workflow are
• familiarity with external data sources: GEO, ArrayExpress, EGA, CellxGene --> don't need to be familiar with every single one but at least data repositories like these
• familiarity with external ontologies: DOID, UBERON, CL, NCBITaxon
• previous biology research experience is helpful, especially with Next Gen Sequencing
• prior experience with cloud environments helpful


Job 2: Skills for semantic technologist
• Demonstrated experience with following tools, Protégé, Semaphore, TopQuadrant
• Experience with RDF, RDFS, OWL, SPARQL, GraphQL
• Knowledge graphs
• Biology background- Bachelors
• Public ontology resources (Bioportal, OLS)

Minimum years of experience is 5+
• Life science background would be a benefit