BeOne continues to grow at a rapid pace with challenging and exciting opportunities for experienced professionals. When considering candidates, we look for scientific and business professionals who are highly motivated, collaborative, and most importantly, share our passionate interest in fighting cancer.

General Description:

The Associate Director, Advanced Analytics – Patient Journey Insights and Predictive Modeling will develop and deliver advanced analytics, AI-enabled insights, and predictive modeling solutions that support data-driven decision-making across Commercial, Medical Affairs, and Clinical Operations. This role will translate complex longitudinal healthcare data into actionable insights across the patient journey, including diagnosis, treatment initiation, access, adherence, persistence, healthcare provider engagement, scientific exchange, and clinical trial acceleration.

This highly collaborative role partners with Commercial, Medical Affairs, Clinical Operations, Market Access, Medical Excellence, Clinical Development, IT, Data Engineering, Legal, Compliance, and external analytics partners to generate high-quality insights, build scalable predictive models, strengthen data and model governance, and embed analytics into strategic and operational decision-making.

Key Responsibilities

Patient Journey Analytics and Predictive Modeling

Lead the design and execution of patient journey analytics that identify key moments of intervention, access barriers, treatment transitions, adherence challenges, persistence opportunities, and unmet needs across priority therapeutic areas.
Integrate and analyze longitudinal healthcare data sources, including claims, prescription, specialty pharmacy, EHR, lab, real-world data, clinical trial operations data, market access data, and third-party syndicated datasets.
Develop predictive models and machine learning approaches that support patient identification, biomarker status, provider opportunity assessment, treatment progression, adherence risk, CT acceleration, and engagement prioritization.
Translate model outputs and patient journey findings into clear recommendations, decision frameworks, dashboards, and executive-ready narratives for Commercial, Medical Affairs, and Clinical Operations stakeholders.
Identify practical AI and advanced analytics use cases, including generative AI, natural language interfaces, intelligent automation, and decision intelligence, that improve insight generation and operational effectiveness.

Cross-Functional Partnership and Insight Translation

Serve as a subject matter expert for patient journey insights and predictive modeling, helping business, medical, and clinical stakeholders translate strategic questions into analytical approaches, data requirements, and measurable outputs.
Partner with Commercial, Medical Affairs, Clinical Operations, Market Access, Medical Excellence, Clinical Development, Data Engineering, IT, Legal, Privacy, and Compliance teams to ensure analytics solutions are relevant, accurate, scalable, and appropriate for a regulated life sciences environment.
Communicate complex analytical findings in clear, compelling ways through presentations, dashboards, data stories, and decision-support materials for senior stakeholders and cross-functional teams.
Champion responsible AI and model governance practices by promoting transparency, explainability, bias awareness, human oversight, fit-for-purpose validation, and appropriate documentation for AI-enabled decision support.

Project Leadership and Capability Enablement

Lead cross-functional analytics workstreams from problem framing and data assessment through modeling, insight generation, stakeholder review, and implementation support.
Provide technical guidance and mentorship to analysts, data scientists, and external partners to improve analytical rigor, reproducibility, and business relevance.
Establish practical standards, reusable frameworks, and best practices for patient journey analytics, predictive modeling, model monitoring, and insight delivery.
Promote adoption of analytics by increasing stakeholder confidence, building analytics literacy, and embedding insights into commercial planning, medical strategy, evidence generation, and clinical operations execution.
Continuously identify opportunities to modernize tools, data assets, workflows, and AI-enabled processes that improve the speed, quality, and scalability of analytics delivery.

Education Required:

Bachelor’s degree required in a quantitative field such as biostatistics, statistics, mathematics, economics, data science, computer science, or a related discipline; Advanced degree preferred

Qualifications:

BA/BS degree with 10 + years of overall experience and 7 + years of experience in advanced analytics, data science, patient journey analytics, commercial analytics, medical analytics, clinical operations analytics, or a related function within the pharmaceutical, biotech, healthcare, or life sciences sector.
Demonstrated experience analyzing longitudinal healthcare data and developing actionable patient journey insights across diagnosis, treatment, access, adherence, persistence, provider engagement, or clinical trial acceleration.
Hands-on experience building, interpreting, and operationalizing predictive models or machine learning solutions using healthcare, real-world, commercial, medical, or clinical operations data.
Strong understanding of relevant data sources, such as claims, prescription, specialty pharmacy, EHR, lab, real-world data, clinical trial operations data, market access data, and third-party syndicated datasets.
Ability to translate complex analytics into clear recommendations for senior stakeholders across Commercial, Medical Affairs, Clinical Operations, technology, data, legal, compliance, and vendor teams.
Working knowledge of responsible AI, model governance, validation, explainability, and appropriate use of AI-enabled decision-support tools in a regulated environment.
Bachelor’s degree in statistics, data science, economics, engineering, business analytics, computer science, public health, epidemiology, or a related quantitative field, or equivalent practical experience.

Preferred Qualifications:

Advanced degree, such as a Master’s, MBA, MPH, or Ph.D., in a quantitative, scientific, technology, public health, epidemiology, or business discipline.
Experience with modern analytics, AI, and data platforms, such as cloud data warehouses, data science workbenches, business intelligence tools, SQL, Python, R, SAS, machine learning operations, generative AI tools, and AI/ML deployment approaches.
Experience developing patient journey frameworks, propensity models, provider or account segmentation, time-to-event analyses, survival models, adherence models, site feasibility models, or enrollment forecasting models.
Strong executive communication skills, including the ability to develop clear narratives, simplify complexity, and present insights to senior leadership and cross-functional audiences.
Familiarity with pharmaceutical data privacy, compliance, governance, responsible AI considerations, and the practical application of AI in regulated life sciences environments.

Supervisory Responsibilities:

This position may manage external vendors, agency partners, or contractors and may provide project leadership or informal guidance to junior analysts; no direct people management is required unless otherwise determined by business need.

Travel:

Up to 20% for team meetings, stakeholder workshops, or business reviews may be needed.

Global Competencies

When we exhibit our values of Patients First, Driving Excellence, Bold Ingenuity and Collaborative Spirit, through our twelve global competencies below, we help get more affordable medicines to more patients around the world.

Fosters Teamwork
Provides and Solicits Honest and Actionable Feedback
Self-Awareness
Acts Inclusively
Demonstrates Initiative
Entrepreneurial Mindset
Continuous Learning
Embraces Change
Results-Oriented
Analytical Thinking/Data Analysis
Financial Excellence
Communicates with Clarity

Salary Range: $145,500.00 - $195,500.00 annually

BeOne is committed to fair and equitable compensation practices. Actual compensation packages are determined by several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, certifications, relevant education or training, and specific work location. Packages may vary by location due to differences in the cost of labor. The recruiter can share more about the specific salary range for a preferred location during the hiring process. Please note that the listed range reflects the base salary or hourly range only. Non-Commercial roles are eligible to participate in the annual bonus plan, and Commercial roles are eligible to participate in an incentive compensation plan. All Company employees have the opportunity to own shares of BeOne Medicines Ltd. stock because all employees are eligible for discretionary equity awards and to voluntarily participate in the Employee Stock Purchase Plan. The Company has a comprehensive benefits package that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness.

We are proud to be an equal opportunity employer. BeOne does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans’ Readjustment Assistance Act of 1974, Title I of the Americans with Disabilities Act of 1990, and any other applicable federal, state or local laws, applicants who require reasonable accommodation in the job application process may contact [email protected].

Associate Director, Advanced Analytics, Patient Journey Insights and Predictive Modeling

Job Description

General Description:

Key Responsibilities

Patient Journey Analytics and Predictive Modeling

Lead the design and execution of patient journey analytics that identify key moments of intervention, access barriers, treatment transitions, adherence challenges, persistence opportunities, and unmet needs across priority therapeutic areas.

Integrate and analyze longitudinal healthcare data sources, including claims, prescription, specialty pharmacy, EHR, lab, real-world data, clinical trial operations data, market access data, and third-party syndicated datasets.

Develop predictive models and machine learning approaches that support patient identification, biomarker status, provider opportunity assessment, treatment progression, adherence risk, CT acceleration, and engagement prioritization.

Translate model outputs and patient journey findings into clear recommendations, decision frameworks, dashboards, and executive-ready narratives for Commercial, Medical Affairs, and Clinical Operations stakeholders.

Identify practical AI and advanced analytics use cases, including generative AI, natural language interfaces, intelligent automation, and decision intelligence, that improve insight generation and operational effectiveness.

Cross-Functional Partnership and Insight Translation

Serve as a subject matter expert for patient journey insights and predictive modeling, helping business, medical, and clinical stakeholders translate strategic questions into analytical approaches, data requirements, and measurable outputs.

Communicate complex analytical findings in clear, compelling ways through presentations, dashboards, data stories, and decision-support materials for senior stakeholders and cross-functional teams.

Champion responsible AI and model governance practices by promoting transparency, explainability, bias awareness, human oversight, fit-for-purpose validation, and appropriate documentation for AI-enabled decision support.

Project Leadership and Capability Enablement

Lead cross-functional analytics workstreams from problem framing and data assessment through modeling, insight generation, stakeholder review, and implementation support.

Provide technical guidance and mentorship to analysts, data scientists, and external partners to improve analytical rigor, reproducibility, and business relevance.

Establish practical standards, reusable frameworks, and best practices for patient journey analytics, predictive modeling, model monitoring, and insight delivery.

Promote adoption of analytics by increasing stakeholder confidence, building analytics literacy, and embedding insights into commercial planning, medical strategy, evidence generation, and clinical operations execution.

Continuously identify opportunities to modernize tools, data assets, workflows, and AI-enabled processes that improve the speed, quality, and scalability of analytics delivery.

Education Required:

Bachelor’s degree required in a quantitative field such as biostatistics, statistics, mathematics, economics, data science, computer science, or a related discipline; Advanced degree preferred

Qualifications:

Demonstrated experience analyzing longitudinal healthcare data and developing actionable patient journey insights across diagnosis, treatment, access, adherence, persistence, provider engagement, or clinical trial acceleration.

Hands-on experience building, interpreting, and operationalizing predictive models or machine learning solutions using healthcare, real-world, commercial, medical, or clinical operations data.

Strong understanding of relevant data sources, such as claims, prescription, specialty pharmacy, EHR, lab, real-world data, clinical trial operations data, market access data, and third-party syndicated datasets.

Ability to translate complex analytics into clear recommendations for senior stakeholders across Commercial, Medical Affairs, Clinical Operations, technology, data, legal, compliance, and vendor teams.

Working knowledge of responsible AI, model governance, validation, explainability, and appropriate use of AI-enabled decision-support tools in a regulated environment.

Bachelor’s degree in statistics, data science, economics, engineering, business analytics, computer science, public health, epidemiology, or a related quantitative field, or equivalent practical experience.

Preferred Qualifications:

Advanced degree, such as a Master’s, MBA, MPH, or Ph.D., in a quantitative, scientific, technology, public health, epidemiology, or business discipline.

Experience with modern analytics, AI, and data platforms, such as cloud data warehouses, data science workbenches, business intelligence tools, SQL, Python, R, SAS, machine learning operations, generative AI tools, and AI/ML deployment approaches.

Experience developing patient journey frameworks, propensity models, provider or account segmentation, time-to-event analyses, survival models, adherence models, site feasibility models, or enrollment forecasting models.

Strong executive communication skills, including the ability to develop clear narratives, simplify complexity, and present insights to senior leadership and cross-functional audiences.

Familiarity with pharmaceutical data privacy, compliance, governance, responsible AI considerations, and the practical application of AI in regulated life sciences environments.

Supervisory Responsibilities:

This position may manage external vendors, agency partners, or contractors and may provide project leadership or informal guidance to junior analysts; no direct people management is required unless otherwise determined by business need.

Travel:

Up to 20% for team meetings, stakeholder workshops, or business reviews may be needed.

More jobs at Beigene

More jobs at Beigene