> Markdown version of [/jobs/ext/2750629-scientist-in-vivo-high-throughput-screening-analytics](https://www.wearedevelopers.com/jobs/ext/2750629-scientist-in-vivo-high-throughput-screening-analytics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Scientist, In Vivo High Throughput Screening & Analytics - **Company:** Gilead Sciences Inc. - **Location:** Philadelphia, PA, United States - **Salary:** $133,195.0 - $172,370.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Computer Programming, Data Files, Data Integrity, Data Reduction, Decision Support Systems, Experimental Data, R (Programming Language), Python (Programming Language), MATLAB, Prism (Software), SQL Databases, Scripting, JMP (Statistical Software), Vba Programming Language, Spotfire - **Published:** September 6, 2026 - **Apply:** https://www.phillyjobs.com/job.asp?id=3380095996&tx=TT4643TTI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * MS with 4+ years of relevant experience; or * BS with 6+ years of relevant experience., * PhD or PharmD in Biotechnology, Biology, Biochemistry, Molecular Biology, Immunology, Biomedical Engineering, Bioengineering, or a related scientific discipline with 0+ years of relevant experience; or * MS with 4+ years of relevant experience; or * BS with 6+ years of relevant experience. * Advanced and current knowledge of scientific principles and techniques in biotechnology, molecular biology, cell biology, immunology, biomedical engineering, analytical development, or a related field. * Demonstrated ability to independently design and execute experiments, troubleshoot methods, interpret data, and define next steps under limited guidance. * Experience with high-throughput screening, assay miniaturization, laboratory automation, automated liquid handling, or scale-down experimental systems. * Hands-on experience with mammalian cell culture, plate-based assays, vector or cell-based characterization assays, and/or analytical method development in a biotechnology, pharmaceutical, or academic research environment. * Experience analyzing and summarizing complex experimental data using appropriate statistical, visualization, or workflow automation tools. * Ability to work effectively in a fast-paced, cross-functional research environment and communicate scientific findings clearly to technical and non-technical stakeholders. * Strong documentation practices, attention to data quality, and commitment to laboratory safety, reproducibility, and rigorous experimental execution. * Ability to provide technical advice, share best practices, and help train or mentor less experienced colleagues in laboratory methods, automation workflows, or data analysis approaches. * Relevant experience may include high-throughput screening, assay development, laboratory automation, vector or cell-based characterization, analytical development, data analysis, or applied research in biotechnology, pharmaceutical, academic, or related R&D environments. * Experience with lentiviral vector production, characterization, or functional evaluation. * Experience with primary immune cell or T-cell assays, transduction workflows, flow cytometry, ELISA/AlphaLISA, BLI/Octet, internalization, binding, or potency-oriented assay formats. * Experience implementing or troubleshooting liquid handlers, schedulers, or integrated systems such as Tecan EVO/Fluent, Hamilton STAR, Beckman Biomek, CyBio FeliX, Opentrons, HighRes, BioSero Green Button Go, Agilent Velocity11, or comparable platforms. * Experience programming or scripting in Python, R, SQL, VBA, MATLAB, or related tools to automate analysis, quality control, visualization, or reporting. * Familiarity with Design of Experiments (DOE), multivariate optimization, assay qualification concepts, or statistical methods used in screening and analytical development. * Experience working in a biotechnology or cell/gene therapy environment with cross-functional partners in Discovery, Process Development, Analytical Development, or Translational Research. * Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams. * Develop Talent - understand the skills, experience, aspirations and potential of their employees and coach them on current performance and future potential. They ensure employees are receiving the feedback and insight needed to grow, develop and realize their purpose. * Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives, and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem. ## Description The Scientist, Research High Throughput Screening & Analytics (HTSA) role is a technical and scientific specialist within Kite Research who designs, executes, analyzes, and improves high-throughput screening, scale-down, and analytical workflows that support in vivo lentiviral vector research programs. The role generates high-quality experimental data and scientific insight across screening campaigns, automated assay workflows, vector and cell-based characterization, and data analysis pipelines. Operating with limited guidance, the Scientist applies scientific judgment to troubleshoot methods, interpret complex data sets, recommend next steps, and communicate outcomes clearly to HTSA and cross-functional partners. This role is expected to combine hands-on laboratory execution with automation-minded workflow development and data-driven decision making. The Scientist will partner with Discovery, Process Development, Analytical Development, and other Kite Research stakeholders to deliver reproducible, decision-enabling data that advances early product and platform development., * Design, plan, and execute high-throughput screening and analytical experiments with limited guidance, including miniaturized and scale-down assay formats that support vector, process, analytical, and functional characterization needs. * Develop, optimize, and troubleshoot automated or semi-automated laboratory workflows using liquid handling, scheduling, plate-based assay, and data capture platforms to improve throughput, reproducibility, and data quality. * Execute and analyze cell-based, vector-based, and analytical assays relevant to in vivo CAR-T and lentiviral vector research, including transduction, vector performance, binding, expression, potency, and related characterization endpoints as appropriate to project needs. * Build or improve data reduction, visualization, and reporting workflows using tools such as Python, R, SQL, VBA, JMP, Prism, Spotfire, or equivalent platforms; apply appropriate statistical and analytical methods to support candidate selection and project decisions. * Analyze and interpret complex experimental data; draw logical, evidence-based conclusions and recommend next steps that enable rapid project decisions across HTSA, Analytical Development, Process Development, and Discovery. * Identify and solve technical problems requiring ingenuity and creativity, including assay variability, scale-down translation, automation failures, data integrity issues, and workflow bottlenecks. * Prepare and present clear technical summaries, reports, data packages, and presentations for functional and cross-functional audiences; contribute to technical reports, publications, patent-supporting materials, or regulatory documentation as appropriate. * Collaborate frequently across Kite Research to align screening plans, sample logistics, assay design, automation needs, and deliverables with broader program objectives. * Maintain accurate, traceable, and well-organized experimental records and data files in accordance with Kite documentation, data integrity, safety, and quality expectations. * Share technical expertise, train colleagues on methods or automation workflows, and contribute to a collaborative, problem-solving culture within HTSA and partner functions. ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Leveraging Large Language Models for Legacy Code Translation: Challenges and Solutions](https://www.wearedevelopers.com/videos/1157-leveraging-large-language-models-for-legacy-code-translation-challenges-and-solutions) - [JavaScript? No. Java Scripts! - Scripting with Java](https://www.wearedevelopers.com/videos/2094-javascript-no-java-scripts-scripting-with-java) - [Building a hypercar from scratch](https://www.wearedevelopers.com/videos/607-building-a-hypercar-from-scratch) - [Intermediate Bitcoin Script](https://www.wearedevelopers.com/videos/25-intermediate-bitcoin-script) - [Designing How Work Feels: The Science Behind Sanofi’s Workplace Experience](https://www.wearedevelopers.com/videos/1848-designing-how-work-feels-the-science-behind-sanofi-s-workplace-experience) ## Related Articles - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [A Guide to Green Tech and Green IT Careers](https://www.wearedevelopers.com/magazine/374-a-guide-to-green-tech-and-green-it-careers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)