Senior Data Scientist

BeiGene

2d•$105,600 - $140,600

About The Position

BeOne’s Data Insights team is seeking a Senior Data Scientist to transform trusted enterprise data into AI-enabled decision intelligence for Clinical Development and Operations. The role combines advanced analytics, AI, domain expertise, and product thinking to develop and improve scalable decision products, intelligent automation, and AI-powered analytical solutions. As a hands-on contributor, the Senior Data Scientist partners with business stakeholders, product managers, data and software engineers, AI scientists, statisticians, and clinical experts to solve complex challenges, identify valuable opportunities, and turn insights into decisions and measurable outcomes. Success is measured by analytical quality, product adoption, business impact, AI-enabled productivity gains, and the ability to make data useful for decision-making. The role applies emerging AI technologies to biotechnology and pharmaceutical challenges to help accelerate drug development and improve patient outcomes.

Requirements

At least 2 years of experience in Data Science, Advanced Analytics, Business Intelligence, Product Analytics, Machine Learning, or a related analytical field.
Strong proficiency in Python and SQL.
Hands-on experience analyzing complex datasets, developing analytical solutions, and building reusable code or tools.
Strong analytical thinking and problem-structuring skills, including the ability to turn ambiguous business questions into structured analyses, insights, and recommendations.
Experience defining and analyzing KPIs, developing performance metrics, identifying trends, and using data to support business decisions.
Ability to communicate complex analytical findings clearly to technical and non-technical audiences.
Ability to collaborate effectively with cross-functional stakeholders.
A proactive, hands-on approach to problem-solving, with curiosity, adaptability, and enthusiasm for learning and applying emerging AI technologies.
A master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Systems, Life Sciences, or a related quantitative field is preferred; equivalent practical experience is also accepted.

Nice To Haves

Experience or hands-on exposure to LLMs, prompt engineering, AI agents, retrieval-augmented generation (RAG), conversational AI, or AI-enabled analytical workflows.
Familiarity with AI-assisted development tools such as Claude Code, GitHub Copilot, Codex, or similar tools.
Exposure to Databricks AI/BI Genie or similar conversational analytics and natural-language data exploration platforms.
Experience prototyping, developing, or improving AI-enabled analytical applications, decision-support tools, or intelligent automation solutions.
Familiarity with AI evaluation methods, human-in-the-loop workflows, model monitoring, or responsible AI practices.
Experience with Databricks, Spark, cloud data platforms, or large-scale data processing and exploratory data analysis.
Experience with R, Posit/RStudio Workbench, Git, collaborative development environments, or automated analytical workflows.
Experience in biotechnology, pharmaceuticals, clinical development, healthcare analytics, or another regulated industry.

Responsibilities

Turn complex business and clinical challenges into actionable insights and AI-enabled decision solutions that improve performance and support patient outcomes.
Design, develop, and enhance analytical products using trusted data, advanced analytics, business context, and AI capabilities.
Apply statistical analysis, predictive modeling, trend analysis, segmentation, and root cause analysis to identify opportunities and risks and support decisions.
Translate analytical findings into clear recommendations and compelling data stories.
Explore and apply emerging AI technologies, including LLMs, AI agents, conversational analytics, and workflow automation.
Build and experiment with AI-powered analytical experiences, including conversational BI, automated insights and narratives, intelligent recommendations, and proactive alerts.
Identify repetitive analytical tasks and develop AI-enabled workflows to improve efficiency, scalability, and user experience.
Contribute to end-to-end decision intelligence product development, from understanding user needs and defining requirements through launch and continuous improvement.
Partner with stakeholders and product managers to identify high-value opportunities and prioritize solutions with meaningful business impact.
Define and track KPIs, product adoption, and business outcomes to guide continuous improvement.
Develop reusable analytical tools, frameworks, and capabilities for use across business functions.
Evaluate the accuracy, reliability, and business usefulness of AI-enabled analytical solutions through testing, evaluation metrics, and user feedback.
Support AI evaluation approaches such as benchmark datasets, human-in-the-loop reviews, and ongoing performance monitoring.
Apply responsible AI principles and appropriate data quality, privacy, and compliance practices in a regulated environment.
Collaborate across Clinical Development, Statistics, Scientific Programming, Medical, Data Engineering, Product Management, and AI Engineering.
Explain analytical concepts and AI capabilities clearly to technical and non-technical audiences.
Experiment with new analytical methods, AI tools, and technologies and apply promising ideas in practice.
Share knowledge, contribute to technical best practices, and mentor colleagues through collaboration and hands-on problem-solving.

Benefits

Medical insurance
Dental insurance
Vision insurance
401(k)
FSA/HSA
Life insurance
Paid time off
Wellness benefits
Eligible employees may participate in the annual bonus plan; commercial roles may participate in an incentive compensation plan.
All employees are eligible for discretionary equity awards and may voluntarily participate in the Employee Stock Purchase Plan.