Sr Analyst, Data Scientist

Gilead Sciences • Foster City, CA

8d • $117,895 - $152,570

About The Position

Gilead is seeking a talented and highly motivated Data Scientist for its Advanced Analytical Technologies team within the Analytical Development organization. The role researches, develops, and operationalizes advanced machine-learning and statistical solutions to improve analytical development across Pharmaceutical Development and Manufacturing. It translates scientific and business challenges into scalable, data-driven applications involving quantitative analytics, predictive modeling, computer vision, and other advanced computational methods. The Data Scientist collaborates with laboratory scientists, data scientists, engineers, project managers, and other stakeholders to deliver robust solutions, promote machine-learning best practices, and strengthen data-driven decision-making.

The role supports the full machine-learning lifecycle, from requirements gathering and exploratory analysis through model development, validation, deployment, monitoring, and improvement. It also contributes to end-to-end algorithm and application development, including software packages, compute environments, model architecture, testing, documentation, and operationalization. The position works across analytical development, manufacturing, IT, and technical development teams, and communicates analyses and model results to scientific and cross-functional audiences.

The salary range is $117,895.00–$152,570.00. The position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary by role), paid time off, and company-sponsored medical, dental, vision, and life insurance plans. Actual compensation may vary based on experience, qualifications, and geographic location.

Requirements

• Bachelor’s degree and 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 a master’s degree and at least 2 years of relevant experience in one of these disciplines.
• Strong Python programming skills, including developing maintainable, reusable, documented, and well-tested analytical or machine-learning code.
• Advanced statistical and computational modeling expertise, including 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 needed to deploy and operationalize machine-learning solutions.
• Strong written, verbal, and visual communication skills, particularly in explaining model performance, limitations, findings, and recommendations.
• Demonstrated collaboration, problem-solving, and project-execution skills in multidisciplinary environments.

Nice To Haves

• Experience applying data science or machine learning in pharmaceutical development, manufacturing, analytical sciences, or another regulated scientific environment.

Responsibilities

• Research and develop machine-learning algorithms for 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, 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 machine-learning, software-engineering, reproducibility, and model-governance best practices to ensure reliable, scalable, maintainable, high-quality deliverables.
• Collaborate with multidisciplinary 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 AI 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 data-driven decision-making, support well-designed experiments, identify organizational capabilities and needs, and advance responsible AI adoption.
• Communicate analyses and model results through reports, visualizations, presentations, and recommendations tailored to scientific and cross-functional audiences.

Benefits

• May be eligible for a discretionary annual bonus.
• May be eligible for discretionary stock-based long-term incentives; eligibility may vary by role.
• Paid time off.
• Company-sponsored medical insurance.
• Company-sponsored dental insurance.
• Company-sponsored vision insurance.
• Company-sponsored life insurance. The job posting also links to additional benefits information, but does not specify those benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level