- Department Expansion
Wonderful opportunity for a Data Scientist at a Global pharmaceutical giant!- The primary responsibility of this role is to provide commercial teams measurable insights into commercial strategies and tactics for key products in key markets. These insights will provide competitive advantage by making better business decisions derived through strategic data analysis and command of complex statistical techniques
- Is responsible for key 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 BU and Marketing leadership.
- 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 etc.
- 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)
- Experience in handling and analyzing various internal and external commercial data types (e.g., sales data sources like IQVIA, Cegedim, patient longitudinal, claims data.)
- Experience in epidemiology
- Experience in Pharma industry
- Data Scientist
- 9:00 - 17:30（Mon ‐ Fri）100% WFH
- 12,000,000 JPY - 16,000,000 JPY per year
- Social insurance, Transportation Fee, No smoking indoors (designated smoking area), etc.
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, etc.
▼ Interview（2－4 times）