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.
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.
We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.
Job DescriptionWe are seeking a talented and highly motivated Data Scientist for our Advanced Analytical Technologies team within the Analytical Development organization. The Data Scientist will research, develop, and operationalize advanced machine learning and statistical solutions that improve analytical development across Pharmaceutical Development and Manufacturing. This role will translate scientific and business challenges into scalable, data-driven applications spanning quantitative analytics, predictive modeling, computer vision, and other advanced computational methods. The individual will collaborate with lab scientists, data scientists, engineers, and project managers to deliver robust solutions, promote machine learning best practices, and strengthen a culture of data-driven decision-making.
Key Responsibilities:- Research and develop machine learning algorithms across quantitative analytics, computer vision, predictive analytics, and advanced statistical modeling to improve pharmaceutical development and manufacturing processes.
- Manage the full machine learning model lifecycle, including requirements gathering, exploratory data analysis, visualization, model development, validation, deployment, monitoring, and continuous improvement.
- Support end-to-end algorithm and application development, including software package development, compute environment configuration, model architecture, code reviews, testing, documentation, and operationalization.
- Translate scientific and business challenges into practical data science solutions with measurable technical, scientific, and operational outcomes.
- Apply best practices in machine learning, software engineering, reproducibility, and model governance to ensure deliverables are reliable, scalable, maintainable, and high quality.
- Collaborate with multidisciplinary technical teams, including data science architects, data engineers, analysts, project managers, laboratory scientists, and application developers.
- Partner with stakeholders in an agile environment to scope, prioritize, plan, design, and execute artificial intelligence and machine learning projects.
- Work cross-functionally with analytical development, manufacturing, IT, and technical development teams to advance AI-driven applications and improve scientific and business outcomes.
- Promote a data-driven culture by encouraging quantitative decision-making, supporting well-designed experiments, identifying organizational capabilities and needs, and advancing responsible AI adoption.
- Communicate complex analyses and model results through clear reports, visualizations, presentations, and recommendations tailored to scientific and cross-functional audiences.
Basic Qualifications:- Bachelor's degree with at least 4 years of relevant experience in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Statistics, Chemical Engineering, or a related discipline.
OR- Master's degree with at least 2 years of experience in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Statistics, Chemical Engineering, or a related discipline.
- Strong Python programming skills, including experience developing maintainable, reusable, documented, and well-tested analytical or machine learning code.
- Advanced statistical and computational modeling expertise, with the ability to select, develop, validate, interpret, and improve models for complex problems.
- Advanced proficiency with Python-based machine learning frameworks and libraries.
- Experience with computer vision, including classical image-processing methods and deep learning approaches.
- Knowledge of data modeling, architecture, pipelines, and infrastructure required to deploy and operationalize machine learning solutions.
- Strong written, verbal, and visual communication skills, particularly when explaining model performance, limitations, findings, and recommendations.
- Demonstrated collaboration, problem-solving, and project execution skills within multidisciplinary environments.
Preferred Qualifications:- Experience applying data science or machine learning in pharmaceutical development, manufacturing, analytical sciences, or another regulated scientific environment is preferred.
The salary range for this position is: $117,895.00 - $152,570.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans*.
For additional benefits information, visit:
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* Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.
For jobs in the United States:Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact for assistance.
For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster.
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Gilead Sciences will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, (c) consistent with the legal duty to furnish information; or (d) otherwise protected by law.
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For Current Gilead Employees and Contractors:Please apply via the Internal Career Opportunities portal in Workday.
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