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The Bioinformatician – NGS (Data Standardization & Platform Integration) will support Large Molecule Discovery by standardizing, validating, and scaling NGS data workflows so sequencing outputs can be reliably reused across research programs and enterprise platforms. This role will focus on making NGS pipelines reproducible, efficient, and ready for integration into existing data systems and downstream analytics. Working closely with bioinformatics principal scientists, data scientists, software engineers, and laboratory scientists, this individual will help ensure sequencing data is well structured, consistent, and suitable for broader use in analytics, machine learning, and platform-enabled research. The role combines workflow optimization, data standardization, and platform integration, and is well suited for someone who enjoys building robust computational systems that improve scale, consistency, and reuse.
Job Responsibility
Standardize, validate, and optimize NGS workflows to support reproducible and scalable sequencing analysis across research programs and data analysis pipelines
Improve pipeline performance, including runtime, memory efficiency, operational reliability, and consistency of outputs
Support development of NGS data models, metadata standards, and structured output formats to ensure sequencing information is captured and stored appropriately for downstream use in the database/CDL and broader informatics ecosystem
Collaborate closely with bioinformatics scientists, data scientists, software engineers, and laboratory scientists to align workflow requirements and integration sequencing data into enterprise platforms for analytics, reporting, and downstream reuse
Support validation, testing, and reproducibility practices that help ensure sequencing workflows are reliable, traceable, and suitable for long-term operational use
Requirements
Doctorate degree PhD
Master's degree with 8+ years of directly related experience
Bachelor's degree and 10+ years of directly related experience
Nice to have
PhD with 5+ years of experience standardizing, validating, and scaling NGS workflows for reproducible use across research programs or enterprise environments
Strong background in workflow performance optimization, including runtime, memory efficiency, and operational stability
Familiarity with workflow management and orchestration tools such as Nextflow or Snakemake
Experience with structured NGS data capture in LIMS for downstream analytics and platform use
Experience integrating bioinformatics outputs into enterprise data platforms and structured repositories with an emphasis on supporting data governance, traceability, lineage, and reproducibility for scientific datasets
Experience working closely with data scientists to ensure scientific data is modeled, saved, and organized correctly for downstream use
Familiarity with containerization and cloud- or HPC-based execution environments