Commercial Data Scientist
Global Multinational Pharma company.
- The primary focus of this opportunity is to provide commercial teams measurable insights into commercial strategies and tactics for key products in key markets. These insights will provide a competitive advantage to Bayer by making better business decisions derived through strategic data analysis and command of complex statistical techniques
- Be responsible for aspects along the data modelling cycle: From definition of business questions and hypotheses, to data sourcing and preparation, model development, and insight generation. Output of these analyses will be the basis for strategic resource allocation by BUand Marketing leadership.
- Manage onshore and offshore resources, as well as in house and external consultants.
- Demonstrating thought leadership and content expertise in advanced analytics to business partners, including development of key training programs
- Develop and optimize ML models in different contexts (Sales, MKTG,Patient data, Communication and Social data)
- Translate complex analytics into actionable recommendations and propose feasible solutions. Communicate in a clear and concise way using the most appropriate approach for each different stakeholder
- Work with business and scientific stakeholders with a clear vision of the final goals and on the business impact
- Collaborate closely with other functions (e.g. Commercial Business Insights, Integrated Multi-channel Marketing) to advice, and support brand marketing or sales teams in various types of advanced quantitative analyses, including but not limited to: Marketing Mix Analysis, Advanced Segmentation & Targeting, Personalized communication, etc.
- 5+ years of experience as a Data Scientist or driving advanced analytics implementation
- Strong analytical skills, team playing, and communication skills
- Experience in data modeling, wrangling and visualization
- Knowledge of SQL and data warehousing platforms
- Very good Knowledge of the most important Machine Learning models (classification, regression, clustering, time-series analysis)
- Knowledge of deep learning models (CNN, RNN)
- Knowledge of at least two of the following languages: Python, R, C/C++, Scala, Julia,Mathematica
- Knowledge of the most common ML/DL frameworks (Scikit-Learn, Stan, Pandas,Tensorflow, PyTorch, Keras, Matplotlib)
- Ability to influence cross-functional teams to impact decision- making; Willingness to "have an opinion" backed up by insight and analytics and the confidence to influence key stakeholders in meeting sand one to one basis.
- Strategic business acumen, focus on results, passion for keeping up with media and technology trends. Strong communication and presentation skills.
- Proven track record of professional success in analytics role
- Passionate team player
- Fluent in English and Japanese (JLPT N2 or above)
Nice to have:
- Experience in epidemiology is a plus
- Experience in Pharma industry is a plus
- Experience with Data Management Platforms is a plus
- Experience in handling and analyzing various internal and external commercial data types (e.g., sales data sources like IQVIA, Cegedim, patient longitudinal, claims data, distribution, demand, units, promotion)
Graduate degree in quantitative field (Statistics, Management Science, Operations, Research, Engineering, Finance, Applied Mathematics, Mathematics, Business Administration, Computer Science, etc.)