Unleash Your Data Science Skills – Join Gilead as a Research Scientist in Bioinformatics!

Gilead Bioinformatics Research Scientist Job – Apply Online

Research Scientist – Bioinformatics

Apply Locations:
United States – California – Foster City
United States – Remote

Time Type: Full time

Posted on: Posted 4 Days Ago

Job Requisition ID: R0040022

For Current Gilead Employees and Contractors:

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At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19, and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination, and a relentless drive to make a difference.

We empower our leaders to step up, share ideas, listen, learn, and lead. We’re welcoming bright, diverse, and imaginative minds; we’re nurturing them to foster an environment of inclusion and growth where innovation is encouraged. We expect our people leaders to model that environment and to focus on creating inclusion, developing talent, and enabling teams.

Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact. Join Gilead and help create possible, together.

Job Description

Research Scientist – Bioinformatics

Position Overview:

The Clinical Bioinformatics and Exploratory Analytics department at Gilead supports drug development and other business use cases by providing analytical, engineering, and visualization solutions for clinical and multi-omics data. You will collaborate across functions to enable scientific and other business exploration and decision-making, including statistical analysis, genomic data processing and analysis, and machine learning. You will lead design, development, and implementation of statistical, bioinformatics, and machine learning methods that integrate large multi-modal datasets to derive quantitative biological insights in support of virology clinical development, translation of clinical findings and other business decision-making. You will also contribute to presentations and publications of clinical genomics and biomarker findings either as conference publications, journal publications, or regulatory documents.

Responsibilities:

• Plays a key role in both internal and external collaborations in the analysis of complex data sets, including but not limited to genomic, protein, and cytokine/chemokine data from patient samples together with clinical outcome data from Gilead’s virology development programs.
• Develops predictive models using statistical techniques and machine learning for analysis of large omics and high-dimensional data from internal, publicly available, commercial and Real-World datasets to enable target identification / assessment, drug combinations, understanding of MOA, disease mechanisms, etc.
• Designs and executes data analysis plans, communicates findings and recommends follow-up actions in multiple settings, including one-to-ones, seminars, group and project meetings.
• Participates in development of team and department-level standards, tools, and templates.
• Develops and implements quality assessments, statistical analysis and data visualization for multi-omics datasets, e.g., RNA-Seq, single cell sequencing, WES, WGS, etc.
• Develops data dashboards, visualizations, and analytical tools to improve visualization, integration, and accessibility of complex clinical data and enable data analysis and exploration by the broader Research & Development organization.
• Provides expertise and technical consultation for external collaborations/partnerships in academia and industry.
• Ensures assigned work complies with established practices, policies, and processes and any regulatory or other requirements.

Requirements:

We are all different, yet we all use our unique contributions to serve patients. Please see the following for the qualifications and skills we seek for this role.

Minimum Education & Experience

• PhD in statistics, mathematics, bioinformatics, genomics, computer science, or related discipline with some general business knowledge and work experience. PhD with 2+ years’ bioinformatics or related experience is preferred.
• MS in statistics, mathematics, bioinformatics, genomics, computer science, or related discipline with 6+ years’ bioinformatics or related experience.
• BS in statistics, mathematics, bioinformatics, genomics, computer science, or related discipline with 8+ years’ bioinformatics or related experience.
• Significant experience working with multi-omics and large-scale biological datasets.
• Significant experience working with a broad range of statistical methods, including machine learning methods.
• Strong programming skills in key languages used by Bioinformatics and Statistics, e.g., R, Python, etc., with proven capabilities to manipulate large and multi-dimensional datasets.
• Significant experience working with cloud computing systems, advanced statistical software and/or visualization tools.
• Strong proficiencies in problem-solving, bioinformatics or other data analytics algorithm design, genomic and proteomic technologies, and high throughput experimental techniques, e.g., next-generation sequencing technologies, single-cell technologies, and/or their applications.
• An understanding of infectious disease and/or immune system biology is preferred.
• Hands-on experience working with clinical or other human-derived datasets is preferred.
• A track record in publications within own field is preferred.

Knowledge & Other Requirements

• Demonstrated ability to be a fast learner.
• Demonstrated ability to be flexible and adaptable to change, to move between projects easily and provide support/expertise where needed.
• Proven analytical abilities with high attention-to-detail as demonstrated through past experiences and/or academic achievements, including statistical knowledge, such as probability theory, statistical power, univariate and/or multivariate analysis, unsupervised and supervised analysis, regression analysis, survival analysis, etc.
• Proven ability to conduct effective and efficient exploratory analysis on large volumes of data and identify key descriptive and inferential properties.
• Strong communication and organizational skills.
• Ability to lead and influence programs, projects, and / or initiatives.
• When needed, ability to travel (~5%).