Clinical Bioinformatics Scientist

Gene by Gene•Houston, TX

About The Position

Gene By Gene is seeking a senior-level Clinical Bioinformatics Scientist to develop and maintain high-throughput genomic pipelines in a regulated clinical laboratory environment (CLIA/CAP). The position will involve transforming raw next generation sequencing (NGS) data into actionable clinical insights, ensuring the accuracy, scalability, and security of diagnostic assays.

Requirements

Doctoral Degree in Bioinformatics, Computational Biology, Statistical Genetics, or a related field with 5+ years post-graduate experience.
Understanding of general molecular biology and genetic laboratory procedures.
Ability to apply theoretical knowledge of genetics towards interpretation of genetic data to generate clinical reports.
Expertise with bioinformatics principles and ability to apply this knowledge towards implementation of genetic analysis programs and clinical report generation pipelines.
Knowledge of clinical laboratory regulatory requirements for clinical diagnostics and reporting, including familiarity with HIPAA, CLIA, NYSDOH CLEP standards, and ACMG variant interpretation classifications.
Understanding of population genetics and statistical modeling to account for ancestry, ethnicity, and environmental factors in the calculation of risk scores for complex traits.
Understanding of genetic imputation and haplotype phasing determination, and ability to ensure that imputed data meets strict quality control thresholds for clinical use.
Familiarity with machine learning for genomic functional prediction and pattern recognition.
Familiarity with multiple NGS instrumentation platforms and their file formats (e.g., Illumina, Ultima Genomics, Complete Genomics, Oxford Nanopore, etc.) and ability to create platform agnostic analysis pipelines, adaptable to various platforms.
Expertise or Familiarity with the following (or similar) environments, databases, coding languages, software suites, data analysis tools, etc.: Command Line, Python, R, Java, shell scripting (Bash), SQL and database administration, Strong command of Linux/Unix environments, Cloud computing (AWS, Google Cloud, or Azure), Containerization (Docker, Kubernetes), Software version control tools (Git), NGS analysis tools and variant annotation databases: FastQC, Samtools, Bamtools, VCFTools, BWA, GATK, ClinVar, gnomAD, Bioinformatics tools for analysis of large-scale genomic data (PLINK, Eagle2, Beagle, etc.), Workflow managers (Nextflow or similar), Genetic databases and reference standard repositories (NCBI GenBank, RefSeq, ENSEMBL, Genome Reference Consortium etc.), Global and population-specific genetic reference panels (TOPMed, 1000 Genomes Project, Haplotype Reference Consortium, GenomeAsia, African Genome Resource, etc.).

Responsibilities

Design, optimize, and validate new automated bioinformatics workflows for genetic variant calling.
Use or develop software to receive, process, and analyze genetic data.
Assess software and programs for suitability to achieve desired analysis goals.
Determine appropriate analysis parameters and thresholds for identification and evaluation of genetic markers of interest.
Design defined analysis protocols within the software for routine use by other data analysts, including pre-set filters and settings.
Validate developed protocols to demonstrate accurate generation and reporting of results.
Write or revise code to aid in the processing or analysis of samples through the lab.
Implement algorithms for detection of SNVs, Indels, CNVs, and structural variants from genetic data using developed analysis pipelines.
Complete and document the analytical validation of bioinformatics tools to meet regulatory requirements for clinical use, including the analytical validity of risk models to satisfy CLIA / CAP / ACMG requirements.
Oversee large-scale genomic datasets, ensuring data integrity, security, and HIPAA compliance.
Establish automated QC metrics to monitor run performance and data integrity.
Work with laboratory directors, clinical geneticists, the research and development team, and IT professionals to integrate and implement bioinformatics tools to fulfill client reporting requirements.
Create clinically validated reporting pipelines for genetic data interpretation, including Monogenic and Polygenic Risk Scores, Pharmagogenomics (PGx) interpretation, and Carrier Screening.
Resolve technical issues in production pipelines to prevent delays in client report generation and delivery.