Qualifications
Responsibilities
Benefits
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Your Contributions (include, but are not limited to):Collaborate with Clinical Development, Clinical Operations, Biometrics, and medical teams to support the design, execution, monitoring, and reporting of clinical trials
Develop and maintain data pipelines, analytical products, and dashboards that make clinical and operational data more accessible, consistent, reliable, and actionable
Identify and build operational metrics, statistical signals, risk indicators, and decision-support tools that help stakeholders detect emerging site, study, vendor, country, or workflow risks early enough to intervene
Translate complex clinical and operational questions into practical technical solutions, including data ingression, transformation, modeling, visualization, monitoring, and consumption through readily accessible tools and technologies
Serve as a technical resource for statistical and numerical methods resource for the team, helping determine whether observed differences, trends, outliers, or anomalies are meaningful, actionable, or likely noise
Apply programming, statistics, visualization, and analytical techniques to support clinical trial oversight, data quality review, 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 analytical techniques for scalable solution design
Build and maintain production solution stacks across controlled multiple environments using Git, pull requests, code review, 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
Bachelor’s degree in Data Science, Computer Science, Engineering, Bio/Pharma Development, or related field and 4+ years in an analytical capacity supporting development and maintenance of solutions OR
Master’s degree in Data Science, Computer Science, Engineering, Bio/Pharma Development, or related field and 2+ years as noted above OR
PhD or equivalent in Data Science, Computer Science, Engineering, Bio/Pharma Development, or related field and applicable academic or applied experience as noted above
Demonstrated passion for practically solving complex clinical, operational, and technical problems with scalable technology
Prior bio/pharma, CRO, medical device, healthcare technology, or similar regulated industry experience highly preferred
Advanced proficiency in Python, R, or other mainstream programming languages
Proficiency in SQL, relational database design and data modeling
Proficiency with data platform products such as Databricks/Snowflake
Proficiency with data exploration and visualization tools such as Tableau, Power BI, R, Shiny, Streamlit, or similar frameworks
Strong practical understanding of statistics, including hypothesis testing, confidence intervals, regression, correlation, trend analysis, outlier detection, variance, and distinguishing meaningful signal from noise
Experience with statistical analysis software and tools such as SAS, R, JMP, SPSS, Python, or similar platforms
Experience with AI/ML, generative AI, NLP, model evaluation, human review, and responsible AI practices
Experience with clean code principles, testing methodologies, Git/GitHub, branching, pull requests, code review, versioning, and collaborative development workflows
Experience with cloud infrastructure, cloud computing platforms, infrastructure-as-code concepts, CI/CD, environment management, monitoring, logging, and scalable deployment patterns
Experience with CDISC standards, clinical data flows, GCP regulatory guidelines, and regulated clinical development processes preferred
Experience with machine learning, AI, predictive modeling, patient stratification, operational risk modeling, and responsible use of AI in clinical data analysis
Familiarity with clinical data capture, trial management, randomization systems, clinical operations data, Real World Data, EHR, and wearable data sources
Familiarity with GxP, validation, change control, audit trails, data integrity, privacy/security, compliance standards, and how those expectations are implemented in controlled technology environments
Ability to work as part of a team, communicate complex analytical and technological concepts to non-technical peers, and manage multiple priorities to meet deadlines
#LI-CL1
The annual base salary we reasonably expect to pay is $103,300.00-$141,000.00. Individual pay decisions depend on various factors, such as primary work location, complexity and responsibility of role, job duties/requirements, and relevant experience and skills. In addition, this position offers an annual bonus with a target of 20% of the earned base salary and eligibility to participate in our equity based long term incentive program. Benefits offered include a retirement savings plan (with company match), paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage in accordance with the terms and conditions of the applicable plans.About Neurocrine Biosciences, Inc.
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