Senior Manager, Advanced Analytics

BeiGene•San Carlos, CA

17h•Hybrid

About The Position

BeOne Medicines is seeking a Senior Manager, Advanced Analytics to serve as a key driver of data-driven decision-making across the Commercial organization. Reporting to the Head of Advanced Analytics, this role is a critical bridge between raw commercial data and strategic execution, translating complex datasets into clear, actionable insights that influence philosophy, strategy, and field-level operations. The Senior Manager will own a broad portfolio of patient-level and market analytics, lead predictive modeling initiatives, and partner cross-functionally to embed analytics into day-to-day commercial workflows. This individual will bring deep technical expertise in machine learning and pharmaceutical data, alongside the business acumen to communicate findings effectively to senior stakeholders. This role requires a strong blend of analytical rigor, technical depth, and collaborative spirit, with accountability for delivering timely, high-quality insights aligned to BeOne's commercial priorities in oncology.

Requirements

BA/BS Degree with 7 + years of overall experience, including 6 years of experience in commercial analytics, data science, or a related field within the pharmaceutical or biotech industry, with demonstrated progression in scope and responsibility.
MA/MS/MBA with 5 + years of experience in commercial analytics, data science, or a related field within the pharmaceutical or biotech industry, with demonstrated progression in scope and responsibility.
Proven experience delivering patient-level and market analytics in a commercial pharmaceutical setting.
Experience operating in regulated industries (life sciences, healthcare, or pharma required).
Prior experience working with or managing third-party analytics vendors and consultants.
Strong analytical skills with the ability to work with complex datasets, interpret trends, and translate analytical outputs into clear business insights.
Proficiency in Python and/or R for data manipulation, statistical modeling, and machine learning.
Strong SQL skills for querying and managing large datasets across relational databases.
Hands-on experience building, validating, and deploying predictive models and machine learning algorithms.
In-depth knowledge of pharmaceutical datasets including Claims, EHR data, specialty pharmacy/specialty distributor (SP/SD) data, and similar sources.
Experience with A/B testing and experimental design methodologies.
Proficiency in MS Office suite (Excel, PowerPoint, Word); experience with data visualization tools (e.g., Dataiku) a plus.
Strong business acumen and understanding of commercial market dynamics in oncology, with the ability to connect data insights to strategic and tactical decision-making.
Demonstrated ability to translate complex analytical concepts into business-relevant insights and recommendations for senior audiences.
Strong stakeholder management and influencing skills across business, medical, and technology functions.
Excellent communication skills, with experience presenting to leadership and cross-functional partners.

Nice To Haves

Experience in oncology commercial markets strongly preferred.

Responsibilities

Own patient-level analytics including adherence, persistency, new patient starts, discontinuations, and comorbidity analyses.
Create and manage longitudinal patient journey models to characterize the market and support fundamental analyses such as targeting and segmentation.
Explore novel real-world data (RWD) sources collaboratively with cross-functional teams to advance the depth and breadth of patient-level insights.
Support high-priority commercial initiatives by integrating insights from secondary data analytics, forecasting, primary market research, and competitive and market intelligence.
Leverage machine learning algorithms and predictive methodologies to build, validate, and implement robust, timely models that are adopted and leveraged cross-functionally.
Experiment with varied predictive algorithms to continually improve accuracy and recall of existing predictive models.
Partner with cross-functional commercial teams to assimilate and drive adoption of model results into tactical execution and pull-through initiatives.
Support A/B testing frameworks and experimental design to evaluate the impact of commercial interventions.
Help drive the advanced analytics roadmap from concept to reality, ensuring alignment with broader commercial strategy and business priorities.
Collaborate with third-party vendors, consultants, and business partners as a primary point of contact, responsible for the development of relevant business rules and appropriate governance.
Translate data into insights and actionable recommendations which drive change in philosophy, strategy, and execution.
Work very closely with other functional teams — including Market Access, Marketing, Sales Operations, and Medical Affairs — to support their analytics needs.
Communicate complex analytical concepts and model outputs clearly to non-technical stakeholders through compelling storytelling and data visualization.
Align analytics initiatives across teams while accounting for varying business needs and timelines.