BIOINFORMATICS SCIENTIST JOB DESCRIPTION

A genomic variant calling pipeline that cannot handle tumor-normal matched specimens, or an NGS assay that ships without validated normalization methods, reaches clinicians with results no one can trust. The Bioinformatics Scientist owns the computational logic that prevents that outcome, translating raw sequencing data into defensible analytical outputs within CAP/CLIA-regulated or research-grade laboratory environments. This role requires both the statistical depth to design rigorous validation experiments and the software judgment to move prototype analyses into production pipelines. The work is specific, consequential, and measurable.

As the Bioinformatics Scientist, you own the design, implementation, and validation of NGS analysis pipelines and genomic algorithms that underpin clinical or near-clinical diagnostics products, directly determining the analytical accuracy that reaches patients and clinicians. You will operate within an interdisciplinary laboratory team that includes molecular biologists, software engineers, and clinical scientists, contributing computational expertise at the stage where biological data becomes reportable evidence.

Career Impact: Expertise developed here, spanning variant calling, assay normalization, and CAP/CLIA-compliant pipeline development, is among the most transferable and valued in the molecular diagnostics market.

Business Impact: The analytical methods this role produces determine whether a sequencing-based diagnostic product clears validation and reaches the patients whose care depends on its accuracy.

Growth Opportunity: Scientists in this function regularly move into principal scientist, bioinformatics lead, or computational platform architect roles as their algorithm development portfolio and publication record grow.

• Design and validate NGS analysis pipelines for clinical or research-grade genomic applications, including variant discovery, CNV detection, and fusion calling.
• Develop novel algorithms and normalization methods to improve assay performance across diverse specimen types and sequencing platforms.
• Analyze high-throughput sequencing datasets to characterize genomic alterations in clinical specimens, including tumor DNA and RNA.
• Implement new computational methods into production pipelines in collaboration with software and laboratory teams.
• Validate bioinformatics workflows through rigorous statistical experiment design, reducing critical variables and increasing analytical hit rates.
• Review and interpret sequencing quality control metrics, producing detailed documentation for all analytical projects to meet regulated environment standards.
• Partner with molecular biologists and clinical scientists to translate bench-level assay requirements into computational specifications.
• Monitor emerging sequencing technologies and computational methodologies to inform pipeline improvement and product roadmap decisions.

• Master's degree in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related quantitative discipline, or equivalent work experience.
• 3 or more years of hands-on bioinformatics experience in a clinical diagnostics, genomic services, or molecular biology product environment, with demonstrated pipeline development accountability.
• Proficiency in statistical modeling and genomic data analysis, including population genetics, variant annotation, and sequencing quality control frameworks.
• Experience developing and deploying analysis pipelines under CAP/CLIA-regulated or equivalent quality-controlled laboratory conditions.
• Demonstrated programming ability in Python and R for data processing, algorithm development, and scientific visualization.
• Experience with next-generation sequencing data types including WGS, WES, targeted panels, and the bioinformatics methods specific to each.
• Strong written and verbal communication skills, including the ability to document analytical methods clearly for cross-functional and regulated-environment audiences.
• Experience with version control, relational databases, and reproducible workflow management for production-grade bioinformatics systems.

• Ph.D. in Bioinformatics, Computational Biology, or a related field, with prior experience contributing to new product introductions in a molecular diagnostics or genomic services setting.
• Experience with advanced genomic variant types including structural variants, complex haplotypes, and somatic alterations in tumor specimens, using tools appropriate to each variant class.
• Familiarity with cloud computing infrastructure and distributed computing environments as applied to large-scale sequencing data processing.
• Publication record or patent contributions in NGS methods, variant calling, or clinical genomics algorithm development.

• Variant calling accuracy rate, measured against reference standards across validated specimen types.
• Pipeline validation cycle time, reflecting how efficiently new analytical methods reach production-ready status.
• Documentation completeness rate for regulated-environment projects, audited against CAP/CLIA or equivalent standards.
• Number of novel algorithm contributions integrated into production pipelines per annual review period.
• Sequencing QC pass rate across active projects, indicating upstream data integrity entering the analytical workflow.
• Typical tools: Scripting and statistical analysis (commonly Python and R); workflow management (commonly Nextflow or Snakemake); version control (commonly Git).

• Base Salary Range: $110,000 to $155,000 annually, depending on degree level and experience.
• Bonus: 8 to 15 percent annual performance bonus, structure varies by employer.
• Equity: RSUs or stock options common at biotech and diagnostics companies, typically vesting over 4 years.
• Health Benefits: Medical, dental, and vision coverage; employer contribution rates vary.
• PTO: 15 to 20 days annually, plus company holidays and sick leave.
• Common Perks: Conference and publication support, professional development stipend, and flexible hybrid scheduling at many employers.

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

Background checks are a standard condition of employment for positions in this field, and offers are contingent on successful completion of that process. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity, or any other characteristic protected under applicable federal, state, or local law. Reasonable accommodations are available to individuals with disabilities throughout the application and employment process. Candidates must be authorized to work in the United States.

The Bioinformatics Scientist leads the design and development of highly multiplexed PCR assays and the bioinformatics innovation strategy for Bio-Rad's Advanced Technology Group, supporting the clinical diagnostics market and multi-omics expansion. Working closely with Molecular Biologists, Biochemistry, Microfluidics, and Engineering teams, this role shapes the genomic and proteomic data infrastructure that underpins Bio-Rad's Reproductive Health product portfolio.

Key Responsibilities

• Provide scientific and technical leadership in bioinformatics to the growing technology development team and lead the bioinformatics innovation strategy.
• Analyze genomic and cfDNA sequencing databases to generate genomic assay sequences and IP linked to dPCR around specific targets in Reproductive Health.
• Build internal processes to make multiplex assay primer and probe design rules more efficient.
• Design validation experiments with the feasibility team powered by statistics to reduce critical variables and increase hits.
• Identify key normalization methods for complex RH applications in the context of ddPCR assay.
• Build proteomic databases on fetal cells for unique surface protein identification to support better enrichment of fetal cells.
• Correlate proteomic and genomic databases for both fetal cells and cffDNA to highlight unique multiomic signatures for earlier detection of pregnancy complications.
• Research and build IP around genomic and proteomic signatures from floating biomarkers such as exosomes, microRNAs, mitochondrial DNA, mRNA, and others.
• Develop data analysis methods and algorithms for early concept, discovery, and feasibility stages.
• Partner closely with Bioinformatics and Software teams in Clinical Diagnostics Groups at Bio-Rad.

Required Qualifications

• M.S. in Bioinformatics, Genetics, Computer Science, Statistics, Mathematics, or BioPhysics with 6+ years of experience, or Ph.D. in a related field with 3+ years of experience.
• 6+ years of experience in genetic analysis, bioinformatics, and computational programming, with preference for NIPT or cell-free DNA applications.
• Proven track record of developing products combining genomics, digital PCR or next generation sequencing, molecular biology, statistics, and bioinformatics algorithms.
• Knowledge and experience of common bioinformatics databases, resources, and tools.
• Proficiency in Python (Flask, FastAPI, Pytest, SqlAlchemy) or SQL and at least one of R, Julia, JavaScript, Java, or C++.
• Strong R, SAS, or Matlab programming skills including data graphing is a plus.
• Hands-on experience with Git and SQL for data management and analysis pipeline development is a plus.
• Excellent verbal and written communication skills, logical and analytical thinking, and ability to multitask and work both independently and on a team.

Embedded within the software and informatics team of the Illumina Clinical Services Laboratory, a CLIA/CAP-accredited facility, the Bioinformatics Scientist leads NGS data analysis and sample management to support lab operations and assay development. Working closely with R&D and cross-functional colleagues, this role delivers the pipeline implementation and documentation that sustains a regulated clinical genomics environment.

Core Functions

• Lead data analysis and review of NGS results and sample management to aid current CLIA lab operations and assay development experiments.
• Leverage existing bioinformatics tools to quickly address data analysis needs.
• Analyze massively parallel sequencing genomic data and support statistical and population genetics analysis of large datasets.
• Work with the Bioinformatics team to implement new analysis methods in pipelines based on R&D prototypes.
• Communicate analysis results and findings regularly to a cross-functional team.
• Produce documentation of data analyses, custom software tools, and software development activities to meet CAP/CLIA regulated environment requirements.

Qualifications and Experience

• Master's degree or 2-3 years of industry experience in Bioinformatics, Computational Biology, Biostatistics, Computer Science, or a related field.
• Experience working with NGS data, specifically WGS, and familiarity with CAP/CLIA regulated environment.
• Experience with variant annotation and filtering to aid in variant interpretation workflows.
• Proficiency in Unix and familiarity with batch job queuing systems such as SGE.
• Proficiency in Python with ability to write readable, well-documented, and unit-tested code.
• Experience with relational database management systems including MSSQL and Postgres, and experience with version control systems such as GitHub.
• Proficiency in R and/or Tableau for data visualization and trending, experience with AWS, and familiarity with containerized analysis software and distributed computing resources.
• Familiarity with Illumina's DRAGEN Bio-IT software.
• Proficient written, communication, and presentation skills with the ability to present to diverse audiences.

Reporting to the Biomedical Data Science department at Bayer Pharma AG, the Bioinformatics Scientist analyzes bulk and single-cell RNA-seq datasets from large cancer patient cohorts as part of the EU-funded IMMUcan consortium. Partnering with pharma partners and academic labs across a global network, this role delivers the computational insights that advance understanding of tumor-immune interactions and support the development of immuno-oncology therapies.

Primary Duties

• Derive key biological insights from patient cohorts and assess the relevance of new targets.
• Analyze bulk and single-cell RNA-seq datasets from large human cancer patient cohorts.
• Set up bioinformatics tools for the analysis and integration of multi-omics data.
• Interact and discuss with pharma partners and academic labs in a global consortium.
• Evaluate, implement, and use state-of-the-art computational methods for integrating data types and interpreting results.
• Strengthen the visibility of research and scientific excellence through publishing and actively engaging with the scientific community.

Skills and Qualifications

• Recently obtained Ph.D. in Bioinformatics, Biostatistics, Informatics, Physics, Biochemistry, Molecular Biology, Molecular Medicine, or equivalent.
• Strong background in data integration, data and knowledge management, data annotation, and big data analysis.
• Previous experience in developing computational biology and bioinformatics methods and proficiency in R or Python.
• Previous experience in single-cell RNA data analysis.
• Track record of publications and presentations showing result-orientation and passion to innovate.
• Fluent in English, both written and spoken.
• High degree of self-motivation and autonomy with excellent team spirit and presentation skills.

Sitting at the intersection of R&D bioinformatics and production-scale software, the Bioinformatics Scientist analyzes sequencing data from Ansa's DNA manufacturing workflows to ensure quality control and operational visibility. Operating across bench science, software engineering, and lab automation teams, this role builds the data analysis tools and engineering practices that are critical to Ansa's commercial success.

Duties

• Work with bench scientists to support R&D-scale and production-scale operationalization of custom molecular biology workflows by analyzing experimental data including sequencing data.
• Develop bioinformatics methods to QC custom workflows and address the team's data analysis needs.
• Work closely with the software team to integrate custom data analysis tools with lab automation efforts to productionize work.
• Select and proficiently use the most appropriate bioinformatics tools and employ the best data engineering practices.
• Collaborate and communicate across teams to support technology built on enzymes, chemistry, and automation.

Experience and Qualifications

• M.S. or Ph.D. in Bioinformatics or an engineering field with Molecular Biology background.
• 3+ years of hands-on experience with sequencing data analysis, preferably third-generation sequencing data.
• Deep knowledge of molecular biology assays and proficiency working with LIMS.
• Fluency in Python and mastery of scientific data analysis tools.
• Expertise in researching, learning, testing, and using state-of-the-art data science and bioinformatics tools.
• Hands-on laboratory experience with sequencing technologies such as Sanger, Illumina NGS, PacBio, and Oxford Nanopore is a plus.

A key member of the Biomarker Sciences Group, the Bioinformatics Scientist supports pre-clinical drug discovery activities including siRNA library design and biomarker hypothesis testing to help drive expansion of Avidity's AOC platform. Collaborating across Research and Development project teams, this role owns the integrated genomic analyses and meticulous documentation that advance the company's therapeutic pipeline.

Functions

• Support pre-clinical drug discovery activities including siRNA library design, off-target analysis, disease model characterization, and biomarker hypothesis generation and testing.
• Collaborate with project teams to design genomic experiments, develop analysis approaches, and independently execute bioinformatics analyses.
• Identify relevant internal and external data and knowledge resources and perform integrated data analyses.
• Document hypotheses, experimental design, analysis methods, and results in a meticulous and compliant manner.
• Organize and present results concisely at regular team and cross-functional meetings.

Position Requirements

• Ph.D. or M.S. in Bioinformatics, Computational Biology, Statistics, Biological Sciences, Genetics, Genomics, or Computer Science with 1-3 years of relevant experience in the pharmaceutical industry or research institute preferred.
• Expertise in the analysis of NGS and microarray data.
• Expertise in R and/or Python, Linux, HPC, cloud computing such as AWS, and version control such as Github.
• Bioinformatics expertise in translational development and RNA therapeutics such as siRNA library design is highly desirable.
• Experience with open source and commercial pathway analysis software and sound knowledge of theoretical and applied statistics.
• Knowledge of current bioinformatics trends, public genomic tools, databases, and utilities, as well as text mining and data mining.
• Experience in presenting data with Shiny app or other interactive data visualization tools.
• Excellent presentation and written and verbal communication skills.

Scientific rigor in human microbiome research depends on the Bioinformatics Scientist, who provides expert support on 16S rRNA sequencing, shotgun sequencing, and microbiome data extraction across a range of tissue types for NIH program activities. Based within MSC's NIH-embedded team in Bethesda, MD, this role advises on scientific papers, mentors postdocs and Ph.D. students, and ensures that microbiome data methodology is integrated effectively into the program's broader scientific activities.

Accountabilities

• Provide scientific support regarding the incorporation of Human Microbiome Data methodology into the activities of the program such as bioinformatics.
• Provide support for and advise on the content of all scientific papers across a range of data types including methods for 16S rRNA sequencing, shotgun sequencing, and extraction of microbiome data from WGS of human tumor and normal tissue data.
• Advise on the content of all scientific papers across a range of tissue types including oral wash, feces, normal and cancerous tissue, and others.
• Assist with the mentoring of postdocs and Ph.D. students.
• Collaborate with program stakeholders to integrate microbiome data methodology into broader scientific activities.

Technical Qualifications

• Master's degree or Ph.D. with a minimum of 8 years of related experience preferred, or a Bachelor's degree.
• 10+ additional years of experience in lieu of an advanced degree.
• Expertise in specialized domains related to bioinformatics.
• Experience working with rRNA sequencing methodology, shotgun sequencing, and microbiome data extraction.
• Experience assisting and mentoring subordinates is useful.

As the Bioinformatics Scientist, this role generates novel ideas for genetic testing, builds bioinformatics pipelines for novel sequencing platforms, and translates R&D work into clinical production analyses within Color's NGS-focused genomics team. The team relies on this work to expand its genomics platform, drive product definition, and deliver actionable clinical insights from sequencing data at scale.

What You'll Do

• Generate and pursue novel ideas for genetic testing and define next clinical product with proof-of-concept data.
• Introduce and incorporate emerging computational methodologies in the bioinformatics codebase.
• Collaborate with laboratory scientists and data scientists to translate R&D work to clinical production analyses.
• Act as domain expert for both internal and external collaborations and assist in troubleshooting with the high-throughput clinical laboratory.
• Adopt algorithms that enable extracting additional actionable clinical insights from sequencing data.
• Create a basic bioinformatics pipeline to evaluate a novel sequencing platform.

Background and Experience

• 5+ years of experience as a bioinformatics scientist or computational biologist or equivalent role.
• Experience analyzing large sequencing datasets to identify variants across the full spectrum including SNV/indel, CNV, inversions, mobile element insertions, and haplotypes.
• Familiarity with a variety of sequencing platforms including short-read SBS, linked-read, long-read, and optical mapping.
• Experience shipping code in a clinical production environment and familiarity with CAP and CLIA guidelines.
• Intermediate proficiency in Python with a high bar for code quality, and experience with high performance and distributed computing systems such as AWS and GCP.
• Familiarity with standard bioinformatics tools such as BWA, GATK, and DeepVariant, and experience with advanced concepts such as graph alignment and genotyping of complex haplotypes.
• Experience running pipelines using workflow engines such as Toil and workflow languages such as CWL or WDL, and experience with version control via GitHub.
• Experience with relevant data science concepts including machine learning and imputation on biological data.
• Strong communication skills with ability to explain technical information to both technical and non-technical collaborators.

Bioinformatics Scientist leads complex data analysis to evaluate exploratory biomarkers and contributes to early clinical development programs in oncology at Bayer, including scientific leadership of stage gate research and identification of novel biomarkers from large multi-layered datasets. Success in the position means representing Bioinformatics in external academic and commercial collaborations, supporting scientific personnel, and maintaining interfaces across TRGs, Clinical Sciences, Statistics, Pharmacometrics, and IT functions.

Strategic Responsibilities

• Responsible for complex data analysis to evaluate exploratory biomarkers and to significantly contribute to early clinical development programs in oncology.
• Lead and provide scientific leadership on highly innovative research projects in Oncology or adjacent indications to reach or contribute to stage gate decisions.
• Identify novel biomarkers using state-of-the-art bioinformatics methods to analyze large and complex datasets.
• Develop, evaluate, implement, and apply novel bioinformatics methods on complex datasets including big data and integration of several data layers.
• Provide data packages and recommendations to support early stage gate decisions in cross-functional biomarker sub-teams.
• Represent Bioinformatics in external collaborations with academic or commercial partners and in external networks.
• Support scientific personnel including post-docs, master students, and Ph.D. students, and maintain interfaces between TRGs, Clinical Sciences, Statistics, Pharmacometrics, and IT functions.

Minimum Qualifications

• Bachelor's or Master's degree with several years of experience, or Ph.D. with first experience in Bioinformatics, Chemistry, Biology, Genetics, Biomedical Engineering, Physics, Computer Science, or a related quantitative discipline.
• Advanced IT and programming skills with familiarity with high performance computing.
• Strong analytical thinking, scientific rigor, and a systematic approach to problem solving.
• Capability to present complex issues clearly and convincingly to project teams and decision bodies.
• High self-motivation, scientific excellence, and commitment to life-long learning.
• Fluent in English, both written and spoken.
• Clear leadership potential with very good soft skills and ability to manage a high degree of complexity.

The Bioinformatics Scientist develops statistical modeling approaches on NGS data for immune-oncology applications and explores signals for early cancer detection from large-scale data at Guardant Health, the leader in liquid biopsy. Working across computational and experimental teams in an interdisciplinary research environment, this role produces the reproducible analyses and documentation that enable breakthroughs in cancer patient care.

Role Responsibilities

• Design, prototype, and analyze statistical modeling approaches on NGS data in the context of immune-oncology.
• Explore and characterize signals relevant to early cancer detection from large-scale data.
• Communicate analysis results to stakeholders across computational and experimental teams.
• Contribute to a highly collaborative work environment through brainstorming sessions and maintaining a motivating environment.
• Develop reproducible analyses for research and development activities and provide written documentation and specifications.

Professional Experience

• Ph.D. in Computer Science, Statistics, Mathematics, Computational Biology, or related fields, or M.S. with 3+ years of relevant experience.
• Experience with analysis of high-throughput NGS data in the context of immunology, immune-oncology, epigenomics, or other applications.
• Background in statistical fundamentals and modeling including inference approaches and iterative model development.
• Experience developing and implementing novel methods in an open-ended data-limited setting.
• Proficiency with a high level scripting language such as Python or R, Linux command-line, and version control tools such as git and GitHub.
• Experience in computational immunology or proteomics is preferred but not required.
• Experience in oncology and liquid biopsy NGS applications is preferred but not required.
• Excellent communication skills in an interdisciplinary environment.

Embedded within the bioinformatics and molecular diagnostics teams at Cepheid, the Bioinformatics Scientist develops novel algorithms for multiplexed PCR primer and probe design and supports the computational pipeline for automated assay design across all stages from planning to commercialization. Working closely with Bioinformatics Engineers and Molecular Biologists, this role advances the technical foundation for Cepheid's multiplexed molecular diagnostic products.

Day-to-Day Responsibilities

• Rapidly prototype novel and innovative algorithms for the design of multiplexed PCR primers and probes compatible with Cepheid's instrumentation and experimental methods.
• Assist Bioinformatics Engineers in the development of a robust computational pipeline for automated and semi-automated assay design.
• Develop rigorous methodologies for analyzing PCR primer performance data, perform analyses, and communicate results to experimental scientists and others in the company.
• Think creatively in a collaborative environment about novel and innovative solutions for difficult assay design problems.
• Analyze data and debug results to identify avenues for future development and improvement.

Education and Experience

• Master's degree in Bioinformatics or a related field with 7+ years of related work experience, or a Doctoral degree with 4+ years of related work experience.
• Proficient and hands-on in Python in a Linux environment, preferably including experience implementing and maintaining bioinformatics pipelines.
• Fundamental understanding of PCR and experience in PCR primer and probe design.
• Experience in the design and/or analysis of molecular diagnostics assays.
• Proactive self-starter with strong analytical and troubleshooting skills and ability to conduct and plan independent projects with minimal supervision.

Reporting to operations and delivery leadership at Tempus, the Bioinformatics Scientist manages data quality assurance and client delivery workflows for cancer genomics bioinformatics data, using SQL, Python, and Bash to retrieve and analyze clinical sequencing outputs. Partnering with scientists, clinicians, and pharmaceutical clients, this role refines the data operations processes that enable external partners to make evidence-based scientific decisions.

Operational Focus

• Field questions and requests from internal stakeholders and external customers including pharmaceutical clients and research partners regarding the Tempus bioinformatics pipeline.
• Retrieve relevant data from various bioinformatics resources using SQL, Python, Bash, and other tools to support data delivery.
• Engage in cross-functional analysis with scientists, clinicians, delivery teams, and operations team management to analyze cancer clinical sequencing data relevant to Partner and Pharma clients.
• Communicate findings in a clear and logical manner to help stakeholders make scientific decisions based on data analysis.
• Produce high quality and detailed documentation for all projects.

Knowledge Skills and Abilities

• Advanced degree in Bioinformatics, Computational Biology, Genomics, or a related field, with Ph.D. in Bioinformatics and/or Computational Biology preferred.
• Significant work experience handling next-generation sequencing data and thorough understanding of bioinformatics data analysis pipelines.
• Work experience in cancer genetics, precision medicine, or molecular biology, with pharma work experience preferred.
• Familiarity with relational database querying including MySQL and Postgres, and demonstrated programming ability in relevant bioinformatic programming languages.
• Familiarity with Python and/or R and strong background in statistical models and analyzing and resolving problematic data.
• Experience with communicating insights and presenting concepts to a diverse audience.
• Experience with cloud computing is a plus.

Sitting at the intersection of drug discovery informatics and cloud-scale NGS data analysis, the Bioinformatics Scientist leads development and maintenance of the DEL informatics pipeline and database at WuXi AppTec's HitS Business Unit. Operating across chemistry, biology, and informatics disciplines, this role develops the data infrastructure and reporting systems that deliver high-quality DEL screening results to clients and improve the screening platform over time.

Job Functions

• Lead the development and maintenance of DNA-encoded library informatics pipeline and database on the cloud compute platform.
• Perform DEL NGS data analysis and reporting for data quality control and drug discovery applications.
• Lead the functional team to support project deliveries and collaborate closely with colleagues across various disciplines.
• Participate in regular internal technical meetings as well as client communication.
• Contribute to internal DEL research and development to improve the screening platform.

Required Qualifications

• B.S. or M.S. in Bioinformatics or Computational Biology, preferably with 1+ year of work experience in industry.
• 1+ year of experience in analysis of NGS data and DNA-sequencing data using differential analysis methods, with understanding of discrete data distribution and signal identification.
• 2+ years of experience in Python and shell scripting.
• Working knowledge of data analysis, statistics, and high-performance database systems.
• Understanding of AWS and other cloud-based compute ecosystems.
• Additional experience in molecular biology, cell biology, drug discovery, cheminformatics, structural biology, and biophysics is a plus.
• Decent presentation, scientific and technical writing, and communication skills.
• Ability to effectively multi-task on a team in a fast-paced environment and meet timelines for client samples and projects.

A key member of the Leonetti and Royer groups at the Biohub, the Bioinformatics Scientist designs automated pipelines and machine learning models to extract quantitative localization patterns from millions of fluorescence microscopy images of protein subcellular localization. Collaborating across engineers, data scientists, and biologists, this role creates the computational infrastructure that enables new discoveries in systems biology at the frontier of computer vision and cell biology.

Engineering Responsibilities

• Design automated pipelines to produce and analyze microscopy image data.
• Lead efforts to quantify changes in protein localization patterns in response to a variety of cellular perturbations such as CRISPR screens, drug treatments, or viral infection.
• Collaborate with engineers and data scientists to help develop machine learning models to extract information from fluorescence microscopy images.
• Explain technical concepts to a multi-disciplinary team of biologists, bioengineers, and data scientists at the Biohub.
• Author publications and mentor junior colleagues.

Qualifications and Experience

• Ph.D. in Computational Biology, Cell Biology, Bioinformatics, Biophysics, or a related discipline, which can be waived for candidates demonstrating exceptional knowledge and experience.
• Demonstrated expertise in image processing and scientific programming in Python including NumPy, SciPy, scikit-image, TensorFlow, and PyTorch.
• Proficiency with light microscopy and biological imaging, and experience with cell and molecular biology techniques.
• Familiarity with professional software development best practices including documentation, version control, and CI/CD pipelines.
• Enthusiasm for systems biology and open-source software.
• Highly collaborative, team-oriented, with excellent written and oral communication skills.

Advancing the clinical application of next-generation optical mapping depends on the Bioinformatics Scientist at Bionano Genomics, who designs and leads analysis of clinical research projects and builds novel visualization tools for large-scale genomic validation studies. Serving as the analytical core of the team, this role produces manuscripts, white papers, and peer-reviewed publications that translate genomic data into validated clinical findings.

Project Responsibilities

• Design and lead the analysis of clinical research projects and perform advanced data analysis on public and proprietary genomics data.
• Design and implement novel tools to analyze and visualize results for large validation efforts.
• Develop and contribute to writing of SOPs and prepare results in figures and data tables.
• Write manuscripts and white papers.
• Present results to collaborators, at scientific meetings, and in peer-reviewed publications.

Experience and Qualifications

• Ph.D. in an area related to Genomics, Computational Biology, or Bioinformatics.
• Minimum of 2 years of relevant industry or research experience in genomics.
• Experience with WGS, WES, or gene panel sequencing and classification, and experience with analysis of clinical data including prioritization and identification of disease-driving variants.
• Knowledge in population or cancer genetics and experience with population- and family-based analysis.
• Experience with microarray platforms, NGS technologies, and their application to de novo assembly and structural variation analysis.
• Experience with one or more of the following: Shell, Python/Perl, and R, along with strong knowledge of genomics databases and knowledge in statistics and modeling.
• Experience with basic molecular biological lab techniques related to the preparation and analysis of genomic DNA such as enzymatic reactions, PCR, and PFGE.
• Strong publication track record.

As the Bioinformatics Scientist, this role performs quality control and analysis on next and third generation sequencing data while developing and implementing data management policies and SOPs for multiple sequencing projects at the National Institutes of Health. The NIH program relies on this work to ensure cost-efficient, well-organized data storage and to support staff across the genomics research operation in Bethesda, MD.

Scope of Work

• Perform quality control on genomic data including next and third generation sequencing long-read sequencing data.
• Perform analyses on next and third generation sequencing and report and interpret quality control and analyses results.
• Develop and implement policies for effective data management and optimize, organize, and assist in establishing cost-efficient data upload and downloads.
• Manage and organize data storage for multiple sequencing projects and prepare detailed reports for management on incoming and outgoing data.
• Create SOPs for data transfers and quality control steps and assist staff members in the daily use of data.

Technical Qualifications

• Master's degree or Ph.D. in Bioinformatics, Computer Science, Computer Engineering, or a related field.
• Experience with next and third generation sequencing data handling and analysis.
• Experience with high performance and cloud computing, and experience with data organization and storage.
• Excellent organizational skills and ability to decipher and organize large amounts of data.
• Excellent communication skills and ability to translate complex problems clearly and in non-technical terms.
• Strong interpersonal skills and ability to work in a team environment.

Bioinformatics Scientist performs data analysis, generates customer reports, and builds customized NGS pipelines for clinical service projects at Azenta Life Sciences, a global leader in automated bio sample management and genomic services. The work directly supports the evaluation and optimization of NGS data analysis solutions across the company's clinical service lines worldwide.

Activities

• Perform data analysis and generate reports for customer projects.
• Develop novel algorithms and build customized pipelines for clinical service projects.
• Build LIMS workflows for operation service lines.
• Evaluate and identify optimal NGS data analysis solutions.
• Conduct literature search for various genomics research areas.

Minimum Qualifications

• B.S. in Bioinformatics with a minimum of 1-3 years of experience required.
• M.S. in Bioinformatics with 0-2 years of experience preferred.
• Experience with NGS data analysis preferred.
• Proficient in BI analysis pipelines and solutions.
• Strong mathematical and analytical skills.

The Bioinformatics Scientist creates integrated biomarker analyses spanning flow cytometry, RNAseq, and Nanostring data, and builds machine learning models for patient stratification in support of Xencor's clinical development and companion diagnostics programs. Working with clinical statisticians, research staff, and external collaborators, this role generates the data packages and visualizations that inform clinical study reports, medical conference presentations, and pre-IND submissions.

Key Responsibilities

• Support data analyses for pre-clinical programs and pre-IND data management.
• Perform data integration of various types of biomarker data such as flow cytometry, RNAseq, and Nanostring from Xencor preclinical and clinical programs.
• Integrate public data sources for internal data mining including CCLE, scRNAseq, and TCGA.
• Build machine learning models for patient stratification using high dimensional data and contribute to development of NGS data processing pipeline.
• Contribute to the development of biomarker, pharmacodynamic, and other specialty-lab sections of clinical protocols including selection of assays and analysis endpoints.
• Collaborate with clinical statisticians to transition biomarker analysis outputs into specifications for study tables, listings, and figures for clinical study reports, publications, and medical conference presentations.
• Curate preclinical and clinical biomarker data and design analyses and visualization on internal biomarker web portal and coordinate collaborations involving biomarker data.
• Represent bioinformatics as an ad-hoc member of clinical study teams and review data collection and sample management procedures for biomarker endpoints as needed.

Skills and Qualifications

• Ph.D. with 3 years of industry experience or Master's degree with 5 years of industry experience in Bioinformatics, Computer Science, Statistics, Mathematics, or a closely related discipline.
• Deep knowledge of high throughput molecular profiling and experience in mining big OMICS data.
• Working knowledge of immunology and oncology.
• Experience with R (preferred) or Python programming, and hands-on experience with flow cytometry and CyTOF data analysis is a plus.
• Experience with RShiny and RMarkdown framework and AWS is a plus.
• Excellent interpersonal, collaboration, communication, and decision-making skills.
• Independent, innovative, and creative thinker with ability to multi-task in a dynamic environment.

Embedded within cross-functional product development teams, the Bioinformatics Scientist supports new product introductions by executing variant discovery, variant calling, CNV detection, and fusion calling analyses, and plays a pivotal role in algorithm and tool development for oncology sequencing applications. Working closely with program management, molecular biology, software, and instrument teams, this role coordinates the translation of new product requirements into prototype and production-level software that expands the company's oncology diagnostics portfolio.

Core Responsibilities

• Support new product introductions focusing on sequencing and analysis strategies for oncology and other novel applications.
• Balance between providing customized data analysis to support bench scientists and improving core sequencing technologies.
• Perform analyses such as variant discovery, variant calling, CNV detection, and fusion calling, then interpret, summarize, and share findings with appropriate teams.
• Work closely with program management, product management, molecular biology, software, instrument, and other bioinformatics teams.
• Play a pivotal role in algorithm and tool development, translating new product requirements into prototype and production-level software, testing and integrating code, and coordinating improvements.
• Provide support for on-market products and use innovative approaches for system improvement and troubleshooting.

Background and Experience

• M.S. with 3+ years of experience or Ph.D. in Bioinformatics, Computational Biology, Statistics, Computer Science, or Biological Sciences, preferably with application experience in oncology, reproductive health, inherited disease, or human genetics.
• Hands-on experience with public cancer genomic data sources such as TCGA, COSMIC, and ClinVar.
• Solid knowledge of next-generation sequencing analysis under the Linux environment, with good understanding of software engineering and data analysis principles.
• Experience with PCR primer design, sequence and motif analysis, and cancer genomics is particularly welcome.
• Proficiencies in a scripting language (Python preferred or Perl), a statistical package (R preferred or MATLAB), and shell-scripting.
• Computational pipeline development and database management, as well as solid background in genomics and statistics.
• Familiarity with product development and/or project management, along with knowledge of Microsoft Office and Atlassian, is a plus.
• Proven track record of scientific publications and scientific conference presentations is a strong plus.
• Effective communication skills for presenting scientific results, working collaboratively in a team, and documenting work.

Reporting to an interdisciplinary team of Biochemists, Bioinformatics Scientists, and Data Scientists, the Bioinformatics Scientist develops novel methods for detecting and analyzing alterations in tumor DNA and RNA derived from clinical cancer specimens, while enhancing existing assay methods for a diagnostic products program. Partnering with Computational Biologists and engineers using massively parallel sequencing technologies, this role executes the algorithm development and data processing that advance cancer diagnostics from early concept through production validation.

Delivery Expectations

• Partner within an interdisciplinary team of Biochemists, Bioinformatics Scientists, Computational Biologists, and Data Scientists focused on developing diagnostic products using massively parallel sequencing of tumor genomic DNA and RNA.
• Contribute to the development of new methods and algorithms to identify and characterize alterations in tumor DNA and RNA derived from clinical cancer specimens.
• Enhance existing methods, improving their assay capabilities as well as their technical robustness.
• Process, analyze, and interpret high volumes of data for the development and validation of methods.
• Monitor and evaluate analytical aspects of new and emerging technologies and present scientific and technical data to colleagues in a clear and cohesive manner.
• Prepare project timetables, schedules, and deliverables and provide independent contributions.

Experience and Qualifications

• Master's Degree in Biochemistry, Bioinformatics, Computational Biology, Computer Science, or a similar discipline with 1+ year of industry or academic medical center professional experience or post-doctorate work.
• Ph.D. in Biochemistry, Bioinformatics, Computational Biology, Computer Science, or a similar discipline with 3+ years of industry experience preferred.
• Strong scientific understanding of molecular biology and genomics, and prior experience with high-throughput sequencing.
• Experience in cancer research including a working understanding of computational approaches for cancer genome analysis.
• Proficiency with programming and scripting languages R and Python, and experience developing algorithms for analysis of biological data.
• Experience contributing to a complex production analytical system and understanding of HIPAA and importance of privacy of patient data.
• Excellent teamwork, time management, and organizational skills with impeccable documentation practices and attention to detail.
• Strong interpersonal skills including collaboration and creative problem solving with ability to present data to a multidisciplinary audience.

Sitting at the intersection of translational cancer research and genomics algorithm development, the Bioinformatics Scientist designs and conducts analyses to improve variant calling and classification systems and translates model system insights into clinical predictors of therapeutic response. Operating across interdisciplinary groups of scientists, engineers, and product developers, this role guides the development of next generation sequencing algorithms that produce clinically actionable insights for cancer care clients.

Areas of Ownership

• Design and conduct analysis to improve variant calling, classification, and analysis systems.
• Translate insight from model systems into predictors and classifiers of therapeutic response and prognosis in clinical cancer care.
• Collaborate with scientists and clinicians to design and perform analyses on cancer clinical sequencing data in order to improve quality of care.
• Work in interdisciplinary groups of scientists, engineers, and product developers to translate research into clinically actionable insights for clients.
• Develop algorithms used to gain insight into cancer variation through analysis of next generation sequencing data.
• Produce high quality and detailed documentation for all projects.

Requirements

• Ph.D. in Cancer Biology or Molecular Biology related to cancer.
• Experience in cancer genetics, immunology, or molecular biology, and experience working with next-generation sequencing data.
• Background in predictive or prognostic algorithm development and strong background in the development of statistical models.
• Computational skills using R, Bioconductor, and/or Python, and demonstrated programming ability.
• Experience with communicating insights and presenting concepts to a diverse audience.
• Self-driven and works well in interdisciplinary teams.