Global Pharmaceutical company is looking for data scientist.

RESPONSIBILITIES

• The primary responsibility of this role is to provide commercial teams measurable insights into commercial strategies and tactics for key products in key markets.
• 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
• 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.
• 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.

REQUIREMENTS

• Graduate degree in quantitative field (Statistics, Management Science, Operations Research, Engineering, Finance, Applied Mathematics, Mathematics, Business Administration etc.)
• 5+ years of experience
• 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 Pharma industry is a plus
• Experience with Data Management Platforms is a plus
• Fluent in English and Japanese (JLPT N2 or above)

#LI-BP1