BIOINFORMATICS ENGINEER JOB DESCRIPTION

A Bioinformatics Engineer is someone who turns raw genomic sequence data into reproducible, decision-ready outputs for clinical research teams. In clinical settings, that definition carries real weight. NYS-DOH accreditation requirements, CAP laboratory standards, and the scrutiny applied to variant detection in patient-derived samples all set a higher bar than research-only environments. The role owns the full pipeline layer - from ingestion of whole exome and genome sequence data through variant annotation and knowledge base maintenance - and answers directly to pathology leadership and principal investigators who depend on those outputs for downstream clinical decisions.

As the Bioinformatics Engineer, you are accountable for designing, operating, and continuously improving NGS data analysis pipelines that support clinical research, quality assurance, and regulatory documentation across a laboratory or research environment. You work within a cross-functional team spanning pathology, computational science, and IT, contributing both engineering depth and scientific judgment to ensure pipeline outputs meet accreditation and reproducibility standards.

Career Impact: Hands-on ownership of clinical NGS pipelines - including variant detection for SNPs, indels, CNVs, and structural rearrangements - builds a credential set that is directly valued in clinical sequencing centers and pharmaceutical research organizations.

Business Impact: Accurate, reproducible pipeline outputs directly determine whether clinical research teams can publish, submit regulatory documentation, or proceed with patient-derived sample analysis on schedule.

Growth Opportunity: Experience spanning whole exome sequencing, whole genome sequencing, and structural variant algorithm development positions you for senior bioinformatics scientist or computational genomics lead roles within 2 to 4 years.

• Design and operate computational pipelines for next-generation sequencing data spanning whole exome and whole genome analysis.
• Develop and refine variant detection algorithms for SNPs, indels, CNVs, inversions, and translocations to support clinical research accuracy.
• Maintain a curated knowledge base of variants and annotations discovered across processed sample sets.
• Collaborate with pathology, IT, and computational teams to implement and validate NGS data analysis systems with appropriate source control.
• Support laboratory accreditation processes by generating analysis results and documentation required by regulatory bodies.
• Monitor pipeline performance and data quality, troubleshooting discrepancies and applying corrections to eliminate root causes.
• Coordinate vendor relationships for technical upgrades and design validation steps to verify system changes before production deployment.
• Enforce documentation standards for transparency and reproducibility across pipeline configuration, process records, and issue tracking.

• Master's degree in bioinformatics, computational biology, computer science, or genetics, or equivalent work experience.
• 3 or more years of bioinformatics experience in a clinical sequencing, research, or pharmaceutical environment, with demonstrated NGS pipeline work.
• Proficiency in scripting and programming for genomic data processing, including experience with high-throughput data formats.
• Knowledge of variant calling methods covering both small variants and structural variants in clinical research contexts.
• Familiarity with containerization and workflow management for reproducible, scalable pipeline deployment.
• Understanding of cloud-based computing environments and experience applying best practices for storage and data management.
• Strong statistical analysis skills and working knowledge of common statistical environments used in genomics research.
• Clear written and verbal communication skills with the ability to produce regulatory-quality documentation and present findings to non-technical stakeholders.

• Prior experience supporting laboratory accreditation processes, including preparation of documentation for state or federal regulatory review.
• Background in algorithm development for structural variant detection, including CNV calling and translocation identification in whole genome data.
• Familiarity with genomics databases and annotation resources used to interpret clinical variant significance.
• Experience mentoring junior engineers or contributing to a formal bioinformatics engineering roadmap within a clinical or research organization.

• Pipeline reproducibility rate, measured by successful re-execution of documented workflows without manual intervention.
• Variant detection concordance rate against validated reference standards across NGS assay types.
• Regulatory submission acceptance rate, reflecting completeness and accuracy of accreditation documentation produced.
• Mean turnaround time from sample ingestion to annotated variant report delivery, measured in hours per batch.
• Number of open data quality issues resolved per sprint cycle, tracking pipeline reliability over time.
• Typical tools: Workflow management (commonly Nextflow or CWL), alignment and variant calling (commonly samtools, GATK, and bwa-mem), containerization (commonly Docker or Singularity).

• Base Salary Range: $95,000 to $130,000 annually, depending on seniority and location.
• Bonus: 5 to 10 percent annual performance bonus, typical for clinical research settings.
• Equity: uncommon in nonprofit research, modest equity possible in commercial clinical genomics firms.
• Health Benefits: medical, dental, and vision coverage standard across clinical and research employers.
• PTO: 15 to 20 days annually, plus federal holidays and institutional closures.
• Common Perks: Conference and continuing education budget, access to institutional HPC resources, and remote or hybrid scheduling where lab presence is not required.

Figures are estimates based on general US market benchmarks and may be outdated. Adjust based on location, company size, and seniority level.

Work authorization in the United States is required for this position, and employment is contingent on successful completion of a background check, which may include verification of credentials and prior employment. Reasonable accommodations are available to qualified individuals with disabilities throughout the application and employment process. All applicants are considered without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other characteristic protected under applicable federal, state, or local law.

The Bioinformatics Engineer at AIOnco owns the design and execution of genomic and phenotype biomarker analysis pipelines, working alongside software engineers to architect a commercially viable AI system for cancer prediction. The role shapes clinical and environmental data processing workflows that feed directly into an AI platform backed by real-world sequencing and medical record data.

Key Responsibilities

• Direct and lead bioinformatics analysis pipelines for interpretation of genomic and phenotype biomarkers.
• Develop pipelines for analysis of medical records and environmental information in conjunction with genomic and phenotype data.
• Work with raw sequencing data and different sequencing technologies including NGS for WGS and WES.
• Implement methods for comparison of results between analyses of different databases.
• Collaborate with software engineers to architect and design a commercially viable AI system.
• Provide input processing for feature selection to predict different types of cancer.
• Gather, review, and analyze academic and industry papers to provide potential inputs into the AI platform.
• Assess the reliability and robustness of results from papers to aid in AI platform architecture and implementation.
• Help debug, deploy, support, and update the AI platform.

Required Qualifications

• Bachelor of Science in computational science or a computationally focused biology discipline, Master's degree or PhD preferred.
• 6 to 8 years of related work and research experience in bioinformatics.
• Understanding of clinical oncology and oncology research.
• Familiarity with liquid biopsy for cell-free DNA and ctDNA from blood samples.
• Programming experience with sequencing read data and genomic data, including languages such as Matlab, Python, C, C++, Java, and Perl.
• Experience with open source tools such as Picard, Samtools, and GATK, and familiarity with FASTA, FASTQ, and BAM files.
• Experience with public databases including TCGA, COSMIC, ENCODE, NCBI, and UCSC.
• Experience with cloud storage and computing such as AWS or Azure using Docker.
• Software development skills utilizing artificial intelligence and machine learning.
• Self-motivated, organized, and results oriented with strong problem-solving and multitasking abilities.

Embedded within QIAGEN Digital Insights, the Bioinformatics Engineer delivers technology-based solutions and customized clinical report templates in Java and HTML to support genomics and genetics data interpretation for biomedical research. Working closely with software developers, customers, and cross-functional QDI departments, this role advances the commercial development and continuous improvement of the Qiagen Clinical Insight platform.

Core Functions

• Consult with researchers to recommend technology-based solutions and determine computational strategies.
• Collaborate with software developers in the development and modification of commercial bioinformatics software solutions.
• Develop clinical report templates in Java and HTML to customize clinical test configurations.
• Provide consultation for customers and third-party LIMS providers to build robust API interfaces into the Qiagen Clinical Insight platform.
• Work collaboratively across QDI departments to facilitate the development of new solutions or improvements on existing solutions.

Qualifications and Experience

• PhD in Bioinformatics, Biostatistics, Computational Biology, Biology, or a related discipline, or Master's degree plus 3 to 5 years of experience in a consultative role.
• Solid track record of research in human genetics or related areas as demonstrated by publications.
• Extensive experience with NGS data, analysis pipelines, and algorithms including variant calling, WGS, WES, and GATK.
• Working knowledge of LIMS and experience with sequencing platforms such as Illumina HiSeq, Illumina MiSeq, Ion Torrent, and Pac Bio.
• In-depth knowledge of RESTful APIs and 3 or more years of experience with Python, Java, and shell scripting.
• Proficiency with HTML and JavaScript, and knowledge of database and SQL preferred.
• Working knowledge of version control tools, JIRA, and Docker.
• Customer-oriented with excellent communication, presentation, and multitasking skills.

Reporting to bioinformatics management, the Bioinformatics Engineer leads the independent development of large-scale cloud-based pipelines for genomics data harmonization and interactive application development across AWS and Google Cloud Platform. Partnering with scientists, principal investigators, and information systems staff, this role enables reproducible, high-quality genomics data to flow reliably from sources to end users.

Primary Duties

• Independently manage and develop large-scale bioinformatics pipelines in a cloud computing environment.
• Facilitate efficient transfer of bioinformatics data from sources to users with benchmarking and data quality checks.
• Troubleshoot data quality issues and implement policies and standards for data quality, completeness, and reproducibility.
• Establish and implement integration and testing procedures following industry best practices for production bioinformatics systems.
• Provide continuous assessment of commercial and open-source bioinformatics data resources and processing solutions.
• Serve as an engineering resource and facilitator across bioinformatics-focused projects involving management, scientists, and principal investigators.
• Mentor lower-tier engineering individuals and contribute to the development of a formal bioinformatics engineering roadmap.
• Maintain and audit all documentation required for transparency and reproducibility of operations.

Skills and Qualifications

• Bachelor's degree in a biological or computational discipline, Master's degree preferred.
• Previous experience in applied bioinformatics, computational, and genomics or proteomics areas.
• Strong UNIX and Linux expertise and ability to independently plan and execute complex pipelines and workflows.
• Knowledge of common NGS and other high-throughput data formats and expertise in Python, R, and Perl.
• Expertise with genomic data resources and analysis tools including NCBI databases, UCSC Genome Browser, and ENCODE.
• Knowledge of cloud computing concepts and applications, including Docker and CWL within AWS and Google Cloud Platform.
• Demonstrated ability to lead discussions with information systems and technology owners to achieve desired bioinformatics outcomes.

Sitting at the intersection of computational science and life sciences research, the Bioinformatics Engineer contributes to the development of informatics applications and scientific workflow systems that deliver new analytical capabilities to scientists across the organization. Operating across IT, research, and external contractor teams, this role builds and communicates best practices for software development and data management that support long-term scientific initiatives.

Duties

• Contribute to the development and ongoing support of informatics applications to deliver new capabilities to scientists.
• Collaborate with scientists to define requirements and develop efficient, well-engineered solutions for scientific problems.
• Develop and communicate best practices for scientific software development and data management.
• Evaluate and deliver emerging technologies for scientific projects and future initiatives.
• Prioritize and coordinate with external contractors for development of specific projects or components.
• Champion the use of automation, CI and CD, workflow, and cloud technologies within scientific domains.
• Assist in authoring of System Development Life Cycle documentation including requirements, architectures, unit tests, and data catalogs.
• Collaborate with system platforms teams to manage and maintain existing scientific applications.

Experience and Qualifications

• Bachelor's degree or higher in Computer Science, Engineering, or Life Sciences, with a minimum of 3 years of work experience.
• Demonstrated experience developing computational solutions to scientific problems in bioinformatics, genomics, or statistical genetics.
• Expert-level programming experience with Python, with PySpark preferred, and experience in a Linux and Unix command line environment.
• Experience working with HPC schedulers such as SLURM and scientific or analytic workflow systems.
• Familiarity with shell scripting, DevOps technologies, and cloud technologies including S3, RDS, and EC2.
• Familiarity with database server and big data platforms such as MySQL, Postgres, MongoDB, Elasticsearch, Hive, and Spark.
• Familiarity with backend web applications in Python or NodeJS, with frontend development in CSS and JavaScript as a plus.
• Strong communicator with the ability to speak effectively to technical and non-technical audiences, with emphasis on quality and technical rigor.

A key member of the consortium's data science team, the Bioinformatics Engineer builds pipelines and software applications for the comprehensive analysis of molecular and clinical datasets with special emphasis on Metabolomics and Proteomics. Collaborating across research, regulatory, and IT functions, this role enables high-quality mass spectrometry-based data to flow through analytical systems and support publication-ready statistical outputs.

Job Functions

• Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
• Determine additional data collection and reporting requirements.
• Design and customize reports based on data in the database and oversee regulatory compliance for utilization of the data.
• Use system reports and analyses to identify problematic data, make corrections, and eliminate root causes for data problems.
• Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
• Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
• Test prototype software and participate in the approval and release process for new software.
• Design and develop software applications involving sophisticated data manipulation.

Education and Experience

• Graduate degree emphasizing engineering, computer science, or statistics preferred, with a Bachelor's degree and 3 years of relevant experience as a minimum.
• Experience with mass spectrometry-based data analysis, preferably in untargeted metabolomics or proteomics projects.
• Proficiency in Python and Linux bash scripting with demonstrated adherence to best practices in software engineering and source code version control using git.
• Experience with cloud computing environments and container systems such as Docker.
• Familiarity with build, release, deploy, and continuous integration frameworks, and the R programming language.
• Biological domain knowledge and understanding of data modeling including ontologies and database design.
• Excellent writing and analytical skills with the ability to prioritize workload and substantial experience with MS Office and analytical programs.

Bioinformatics Engineer develops and operates computational pipelines for whole exome and genome sequence data analysis across both research and operational modalities at the Simons Foundation in New York City. The work directly supports clinical research teams by advancing variant detection algorithms and maintaining an annotated knowledge base of genomic variants discovered across processed samples.

Accountabilities

• Design, develop, and operate computational pipelines for next-generation sequencing data.
• Work on both large-scale projects and small custom tasks spanning a wide variety of analysis problems.
• Develop new and improve upon existing algorithms for variant detection including SNPs and indels.
• Develop methods for structural variant detection including CNVs, inversions, and translocations for clinical research purposes.
• Develop and maintain a knowledge base of variants and annotations discovered in processing of samples.

Background and Experience

• Master's degree or higher in bioinformatics, computational sciences, or a related field.
• Over 3 years of work experience in a research and development setting in bioinformatics.
• Extensive knowledge of computational genomics and experience with next-generation sequencing data and high-throughput data analysis.
• Advanced programming skills in Python and strong background in algorithm development, statistical methods, machine learning, and distributed computing.
• Experience in a Linux and Unix cluster environment, with familiarity with C++, Perl, Matlab, and R desirable.
• Outstanding personal initiative with excellent verbal and written communication skills and the ability to work effectively as part of a team.

Reliable NGS operations across the Department of Pathology depend on the Bioinformatics Engineer, who implements and maintains analysis pipelines for next-generation sequencing data while supporting quality assurance and NYS-DOH accreditation processes. Based within the Molecular Pathology team, this role serves as a hands-on technical resource coordinating with computational, IT, and vendor partners to sustain and improve clinical sequencing workflows.

Scope of Work

• Work closely with team members to identify, develop, implement, and support testing of informatics systems needed for NGS workflows and other molecular lab assays.
• Collaborate with computational and IT teams to implement, test, and maintain systems for NGS data analysis, reporting, database repositories, and data storage with source control.
• Analyze performance of the bioinformatics infrastructure and provide day-to-day assistance to Molecular Pathology's NGS operations.
• Support the accreditation process of new NGS tests with New York State Department of Health by providing appropriate analysis results and documentation.
• Work with vendors regarding technical support and upgrades and design appropriate steps to test and validate those upgrades.
• Support multiple projects simultaneously, participate in management strategic planning, and develop new procedures and project plans.

Technical Qualifications

• Master's degree in computer science, software engineering, bioinformatics, or genetics, or a Bachelor's degree with extensive prior experience.
• Experience in processing next-generation sequencing data, preferably in a clinical sequencing center or pharmaceutical and biomedical company.
• Solid computational skills including Python or Perl scripting and solid knowledge of bioinformatics tools such as samtools, GATK, bwa-mem, and IGV.
• Knowledge of workflow languages and frameworks such as CWL and Nextflow, and containerization platforms such as Docker and Singularity.
• Knowledge of cloud-based solutions on providers including AWS, Azure, Google Cloud, and OpenStack.
• Knowledge of statistical analysis and familiarity with statistical environments such as R and Bioconductor and SAS.
• Familiarity with commonly used genomics databases such as COSMIC and dbSNP, and basic knowledge of molecular biology and genomics.
• Familiarity with system administration and networking.

As the Bioinformatics Engineer, this role leads the design and execution of automated verification frameworks and continuous integration pipelines for secondary analysis software across local and cloud environments. The engineering team relies on this work to ensure that NGS-based data analysis tools meet formal release standards and Software Development Life Cycle requirements.

Key Deliverables

• Partner with software and bioinformatics developers and domain experts to design, perform, and improve verification tests for secondary analysis on local and cloud systems.
• Design and implement automated software verification frameworks and scripts.
• Develop, improve, and maintain automation frameworks and continuous integration pipelines.
• Develop tools and utilities for bioinformatics verification and validation.
• Work independently in cross-functional teams to lead the testing effort for data analysis software.
• Prepare necessary test artifacts required for formal software and product release.
• Carefully analyze and report test results and participate in code and design reviews.
• Ensure Software Development Life Cycle procedures are followed.

Position Requirements

• Bachelor's degree with a minimum of 5 years of related experience, or Master's degree with 3 years, or PhD without experience.
• Experience in scripting languages such as Python and strong software background including low-level systems and algorithmic complexity.
• Familiarity with databases, cloud computing, and web services.
• Understanding of genetics, NGS techniques, and human genome analysis.
• Previous working experience involving bioinformatics software development or testing.
• Proven skills for writing verification plans, protocols, reports, and all aspects of documentation required for formal product release.
• Detail-oriented, analytical, customer-focused, and team-oriented with good verbal and written communication and troubleshooting skills.