Senior Manager, Applied Innovation, Computational Clinical Applications

BeiGene 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 Senior Manager, Computational Clinical Applications will report directly to the Director, Applied Innovation Pathology and is a member of the Applied Innovation Team, a highly innovative and entrepreneurial team driving solutions to clinical trial inefficiencies, rising costs of drug development, lack of technological advances in healthcare/pharma tech, and fragmented data silos. The incumbent will work cross-functionally to solve complex problems and develop artificial intelligence (AI) technologies to advance novel therapeutic development and healthcare delivery. Through a robust informatic approach that is coupled with expert understanding of oncology, computational analysis and mathematical modeling, the incumbent will pioneer and develop innovative solutions and data-driven approaches to drive impactful changes with the rapidly evolving global pharmaceutical and healthcare landscapes. Essential Functions of the job: Work closely with subject matter experts, machine learning engineers, statisticians, physicians, and commercial strategists to develop AI/ML tools and provide insights, evidence, and solutions through data science, mathematical and other forms of quantitative modeling. Design, develop and execute AI/ML research projects using various types of pre-clinical data and patient-level real world data collected from electronic medical records, laboratory results, gene expression data, mutation data, genetic markers, and medical images. Create use cases for collaborations with Academia and Industry research labs that will lead to external publications of proven and tested AI/ML solutions. Analyze high dimensional and unstructured datasets, draw conclusions, define recommended actions, and report results across stakeholders at all levels. Oversee junior engineers and external collaborators on AI projects. Demonstrate good judgment when making technical trade-offs between short term technology needs and long-term business needs Strong track record of analysis and fact-based decision-making Strong scientific acumen and complex problem-solving skills Highly analytical, with strong data management skills Strategic mindset with high intellectual capability, agility and adaptability Results oriented with a propensity for innovative thinking Ability to influence without authority and establish/maintain credibility with senior individuals/audiences Resourceful, decisive and proactive; must be able to manage multiple priorities in a fast-growing organization Sound judgment, high integrity and ability to maintain strict confidentiality Strong consultative and communication skills; must be able to formulate cohesive strategic arguments and respectfully challenge in a group of experts Effective stakeholder and relationship management experience; able to interact and build trusted relationships with all levels of employees, especially senior leadership Education Required: PhD degree in in a quantitative field such as Computer Science, Engineering, or Statistics and minimum 2-3 years of post-graduate work experience, either in industry or academic post-doctoral research, preferably in computational pathology Supervisory Responsibilities: Yes Competencies: Ethics - Treats people with respect; Inspires the trust of others; Works with integrity and ethically; Upholds organizational values. Planning/Organizing - Prioritizes and plans work activities; Uses time efficiently. Completes administrative tasks correctly and on time. Follows instructions and responds to management direction. Communication - Listens and gets clarification; Responds well to questions; Speaks clearly and persuasively in positive or negative situations. Writes clearly and informatively. Able to read and interpret written information. Teamwork - Balances team and individual responsibilities; Gives and welcomes feedback; Contributes to building a positive team spirit; Puts success of team above own interests; Supports everyone's efforts to succeed. Contributes to building a positive team spirit; Shares expertise with others. Adaptability – Able to adapt to changes in the work environment. Manages competing demands. Changes approach or method to best fit the situation. Able to deal with frequent change, delays, or unexpected events. Technical Skills - Assesses own strengths and development areas; Pursues training and opportunities for growth; Strives to continuously build knowledge and skills; Shares expertise with others. Dependability - Follows instructions, responds to management direction; Takes responsibility for own actions; Keeps commitments; Commits to long hours of work when necessary to reach goals; Completes tasks on time or notifies appropriate person with an alternate plan. Quality - Demonstrates accuracy and thoroughness; Looks for ways to improve and promote quality; Applies feedback to improve performance; Monitors own work to ensure quality. Analytical - Synthesizes complex or diverse information; Collects and researches data; Uses intuition and experience to complement data. Problem Solving - Identifies and resolves problems in a timely manner; Gathers and analyzes information skillfully. Project Management - Communicates changes and progress; Completes projects on time and budget. Computer Skills: Programming experience with at least one modern language such as R, Python, Java, C, C and experience using TensorFlow, Pytorch, and other data science, data analysis, and visualization software. Other Qualifications: Strong experience in machine learning model development, model validation and model implementation for clinical applications. Command on fundamentals of analytics, mathematical modeling, machine learning with proven track record (e.g., publications in top-tier journals, presentations at top conferences, patents, or awards). Experience building predictive models for pathology or oncology indications. Experience working with a variety of patient data modalities (e.g., IHC, radiology, single cell genomics, proteomics, digital pathology, patient reported). Travel: Minimal travel, 1-2 times per year We are proud to be an equal opportunity employer and we value diversity. BeiGene 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.