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Director Variant Analyst Jobs in Oregon (NOW HIRING)

Data Visualization Engineer 4

Beaverton, OR · On-site

$119K - $143K/yr

... variant data sources and be able to trace back to the source of truth from code - Will work with ... on direct team: principal engineers; domain partners (leadership, VP level); other software ...

Senior Product Manager, Clinical Genomics

OR · On-site +1

$126K - $166K/yr

... analysis workflows including variant interpretation, clinical review, and reporting. As Natera ... Proven ability to drive alignment across highly matrixed organizations without direct authority ...

Expert knowledge of bioinformatics tools including mapping, variant calling, CNV analysis and ... Experience managing one or more direct/indirect reports. * Exceptional communication skills ...

Director Variant Analyst information

What is a director variant analyst?

A Director Variant Analyst is a senior professional responsible for overseeing the analysis and interpretation of genetic variants within an organization, typically in a clinical or research genetics setting. They lead teams that evaluate genetic data to determine the clinical significance of DNA sequence variations, which is crucial for diagnosing genetic disorders or informing personalized medicine. The director collaborates with scientists, clinicians, and laboratory staff to ensure the accuracy and quality of genetic variant analysis and reporting. They may also contribute to the development of protocols, implementation of new technologies, and compliance with industry regulations. This role requires deep expertise in genetics, bioinformatics, and leadership.

What are the key skills and qualifications needed to thrive as a director variant analyst, and why are they important?

To thrive as a Director Variant Analyst, you need advanced expertise in genomics, variant interpretation, and bioinformatics, often supported by a PhD or equivalent experience in genetics or molecular biology. Familiarity with next-generation sequencing (NGS) platforms, variant annotation tools, and clinical databases, along with relevant certifications such as board certification in clinical molecular genetics, is highly valued. Strong leadership, decision-making, and communication skills are critical for managing teams and collaborating across departments. These competencies ensure accurate and efficient analysis of genetic data, drive innovation, and support high-quality clinical or research outcomes.

What are the main challenges a director variant analyst faces when leading a genomics team?

A Director Variant Analyst often navigates challenges such as managing diverse teams of bioinformaticians and geneticists, ensuring data accuracy amidst rapidly evolving technologies, and balancing project deadlines with regulatory compliance. They must facilitate effective communication between research, clinical, and IT departments, especially when interpreting and reporting complex genomic data. Additionally, staying current with advancements in variant interpretation and integrating new tools while maintaining operational efficiency is a key aspect of the role.

What is the difference between Director Variant Analyst vs Variant Analyst?

AspectDirector Variant AnalystVariant Analyst
CredentialsBachelor's degree, often with experience in data analysis or geneticsBachelor's or higher in biology, genetics, or related field
Work EnvironmentLeadership role in labs or healthcare companies, overseeing projectsHands-on data analysis in labs or research settings
Industry UsageUsed in biotech, healthcare, and research organizationsCommon in genetics labs, research institutions, and healthcare

The main difference is that the Director Variant Analyst typically holds a leadership position with strategic responsibilities, while the Variant Analyst focuses on data analysis and research tasks. Both roles require relevant credentials and are integral to genetics and healthcare industries, but the Director role involves overseeing teams and projects.

What are the most commonly searched types of Variant Analyst jobs in Oregon?

The most popular types of Variant Analyst jobs in Oregon are:

What cities in Oregon are hiring for Director Variant Analyst jobs?

Cities in Oregon with the most Director Variant Analyst job openings:

Associate Director of Bioinformatics (Women's Health and Organ Health)

Natera

OR • On-site, Remote

Full-time

Posted 18 days ago


Natera rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

57th of 120 rated laboratories


Job description

Natera is seeking an Associate Director to lead a team of Bioinformatics Scientists in our Women's Health and Organ Health research organization. You will oversee the scientific planning and execution of research and assay-development of diagnostic projects, and you will be responsible for creating production-ready pipeline components. You will manage your team and its professional growth, the research strategy behind new product development, and the handoff of research work into production. 

The role calls for deep experience in algorithm and assay development, NGS data processing across multiple modalities, and the full life cycle of diagnostic product research and development in a regulated (CLIA) setting. You will evaluate new technologies and NGS assays, implement methods to optimize performance, and help define the product profile from a bioinformatics perspective, with input from R&D, Product, and Laboratory Directors.

Primary Responsibilities:

Team Leadership and Development: Lead and mentor a team of Bioinformatics Scientists. Own their professional growth, their responsibilities, and the standard the team holds itself to.

Research Strategy: Own the research strategy behind new product development, from scoping through execution, working with cross-functional stakeholders on what the team takes on and in what order.

Assay Science: Lead bioinformatics analysis for assay development and optimization, and troubleshoot experiments alongside laboratory scientists. This spans multi-omic approaches including methylation and fragmentomics and other cell-free DNA (cfDNA) derived features. It also spans short-read and long-read sequencing and both hybrid-capture and amplicon target enrichment.

Study Design and Data Quality: Partner with laboratory teams on study design at the research and feasibility stage, covering new technology assessment, optimization, and performance determination. Make sure the resulting data holds up before anyone builds on it.

Analysis Method Improvement: Advise and prototype improvements to analysis pipelines, including variant detection, quality control, and modality-specific processing: methylation calling, fragment-size and end-motif analysis, error suppression for deep targeted panels, and structural-variant calling.

Production Readiness and Handoff: Move research prototypes into stable production workflows. Hold the team to software engineering practice, including version control, testing, continuous integration and delivery, and containerization. Automate the routine parts of research data management, pipeline execution, and reporting so the team's time goes to science.

Ways of Working: AI is a routine part of the work here. As the leader of this team you set what correct use looks like: what an agent may conclude on its own, and what requires a scientist to sign off. We do not screen for prior experience with these tools, and many strong candidates come from environments where they were restricted; we provide the tooling and the ramp time.

Cross-functional Partnership: Work with data science, molecular biology, pipeline engineering, biostatistics, quality assurance, and laboratory operations on new products and on the transition of research work into production. Act as the subject-matter expert those groups come to, and explain findings and the roadmap clearly at every level of the company.

What success looks like after a year:
  • The team has a research roadmap you own, and progress against it is visible outside the team.
  • You independently advise and guide research strategies in cross functional settings.
  • New analysis methods from your team are implemented within production code and demonstrate expected performance on benchmark studies..
  • You and team members become trusted experts that other functions direct their hard questions to, and can independently support decision making.
  • AI agent-assisted work is normal on the team, with a standard for it that you set.
Qualifications:
  • Ph.D. in Bioinformatics, Computational Biology, Computer Science, Mathematics, Engineering, Biostatistics, or a related field. (An M.S. with equivalent experience considered).
  • 7+ years in bioinformatics, including 3+ years leading scientists and working across functions.
  • Demonstrated ownership of a team that took scientific research into real clinical use, not only to a result.
  • Demonstrated experience developing or scientifically guiding diagnostic sequencing assays.
Knowledge, Skills, and Abilities:What we are screening for
  • Deep expertise in next-generation sequencing analysis: hybrid-capture or amplicon-based target enrichment designs, sequencing quality control, secondary analysis, and variant calling.
  • Experience with cell-free DNA sequencing and other omics data, especially in a diagnostics setting. Preferred to have some exposure to multiomics types : methylation, fragmentomics, or related cfDNA signals.
  • Working  knowledge of how a diagnostic product moves through development in a regulated, accredited setting, including the practices and standards that apply.
  • Strong Python, programming, and data analysis skills.
  • Fluency in exploratory data analysis and visualization on complex data sets, and the ability to translate findings into actionable recommendations.
  • Understanding of sequencing workflows from sample extraction through the instrument, deep enough to tell a biology problem from an analysis problem.
  • A demonstrated record of assessing a new platform, assay chemistry or method against established benchmarks..
  • Clear communication of technical detail to people who do not share your background.
  • The ability to run several objectives and timelines at once without close supervision.
Strong candidates may also have
  • Long-read sequencing (PacBio HiFi, Oxford Nanopore) in addition to short-read (Illumina).
  • R, shell scripting, or Java.
  • Cloud computing (AWS, GCP) and workflow orchestration (Snakemake, WDL, Nextflow, Cromwell).
  • Containerization (Docker, Kubernetes) for reproducible, production-grade analyses.
  • A record of conference presentations or peer-reviewed publication.
  • A desire to work in a fast-paced environment where a small team has high impact.

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