Sr. Data Scientist, Clinical Data Solutions

Based onsite in San Diego, CA, the Sr. Data Scientist, Clinical Data Solutions at Neurocrine Biosciences develops scalable data pipelines, analytical products, and automation to enable clinical teams to design, run, monitor, and analyze trials while optimizing safety, efficacy, quality, and efficiency. The role collaborates across Clinical Development, Clinical Operations, Biometrics, and IT to translate complex clinical and operational data into actionable outputs for decision-making.

• Collaborate with Clinical Development, Clinical Operations, Biometrics, and medical teams to support trial design, execution, monitoring, and reporting.
• Build and maintain data pipelines, analytical products, and dashboards that improve the accessibility, consistency, reliability, and actionability of clinical and operational data.
• Create operational metrics, statistical signals, risk indicators, and decision-support tools to help stakeholders identify emerging site, study, vendor, country, or workflow risks early enough to intervene.
• Translate complex clinical and operational questions into practical technical solutions, covering data ingestion, transformation, modeling, visualization, monitoring, and consumption via accessible tools.
• Serve as a technical resource for statistical and numerical methods, helping determine whether observed differences, trends, outliers, or anomalies are meaningful, actionable, or likely noise.
• Apply programming, statistics, visualization, and analytics to support trial oversight, data quality reviews, operational performance monitoring, patient stratification, predictive modeling, and exploratory analysis.
• Develop and enhance AI-enabled, biomarker, translational, and digital measurement solutions that improve clinical review, automation, risk detection, and decision support.
• Provide technical guidance and support to team members, promoting best practices for data organization, code development, and scalable solution design.
• Build and maintain production solution stacks across controlled environments using Git, pull requests, code reviews, CI/CD, release documentation, and change control practices.
• Optimize analytical solutions and cloud-based infrastructure to improve performance, reliability, usability, security, scalability, and cost efficiency.
• Maintain enhancement backlogs, technical documentation, data definitions, business rules, validation evidence, and solution roadmaps to support deployed products and future improvements.

• A Bachelor's degree in data science, computer science, engineering, bio/pharma development, or a related field with 4+ years in an analytical role supporting the development and maintenance of data solutions; or
• A Master’s degree in the same disciplines with 2+ years of relevant experience; or
• A PhD or equivalent with applicable academic or practical experience.
• A demonstrated interest in solving complex clinical, operational, and technical problems with scalable technology.
• Prior experience in bio/pharma, CRO, medical devices, healthcare technology, or other regulated settings is highly preferred.
• Advanced proficiency in Python, R, or other major programming languages.
• Strong skills in SQL, relational database design, and data modeling.
• Experience with data platform products such as Databricks or Snowflake.
• Experience with data exploration and visualization tools such as Tableau, Power BI, R, Shiny, Streamlit, or related frameworks.
• Solid grasp of statistics, including hypothesis testing, confidence intervals, regression, correlation, trends, outlier detection, variance, and distinguishing meaningful signals from noise.
• Experience with statistical analysis software and tools such as SAS, R, JMP, SPSS, Python, or equivalent platforms.
• Experience with AI, machine learning, generative AI, NLP, model evaluation, human review, and responsible AI practices.
• Familiarity with clean code principles, testing methodologies, Git/Git Hub, branching, pull requests, code review, versioning, and collaborative development workflows.
• Experience with cloud infrastructure, infrastructure as code, CI/CD, environment management, monitoring, logging, and scalable…