Data Scientist

About Job

We are seeking a highly motivated and experienced Data Scientist to join our dynamic team. In this role, you will leverage advanced analytics, machine learning, and statistical modeling techniques to extract actionable insights from complex commercial datasets. You will play a pivotal role in shaping our commercial strategies, optimizing omnichannel engagement with customers, enhancing marketing and fieldforce effectiveness, and driving overall business performance within the pharmaceutical landscape. You will collaborate closely with cross-functional teams (especially Digital, GTM and BUs) to translate business challenges into data-driven solutions and communicate findings and impact effectively.

Key Responsibilities

• Design, develop, and implement advanced analytical models (e.g., segmentation, recommendation systems, operations research, forecasting and causal inference) to optimize omnichannel engagement and enhance commercial operations

• Measure, track, and report on the impact and effectiveness of digital solutions and commercial initiatives using robust analytical frameworks

• Collaborate effectively with cross-functional teams to understand business requirements, define analytical scope, and present insights in a clear and compelling manner

• Stay abreast of the latest advancements in data science/AI and their applications in pharmaceutical industry trends to continuously innovate and improve analytical methodologies

About You

• Master's degree or PhD in a quantitative field such as Statistics, Economics, Mathematics, Operations Research, Data Science, Computer Science, or a related discipline

• Minimum of 5 years of hands-on experience in data science, preferably within a commercial context (marketing/CRM analytics), especially in the healthcare industry

• Proven expertise in transforming complex datasets into actionable business insights and influencing strategic decision-making

• Experience with impact analysis, including experimental design (A/B testing) and causal inference methodologies

• Strong proficiency in programming languages commonly used in data science (Python, R), along with advanced SQL skills

• Experience with statistical modeling, machine learning techniques, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch). Experience with operations research and optimization frameworks is a plus

• Strong communication and presentation skills in both English and Mandarin, with the ability to translate complex technical concepts for non-technical audiences

• Demonstrated ability to manage multiple projects simultaneously and collaborate effectively in a cross-functional team environment