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Data Scientist / Senior Data Scientist 




  • Customer micro-segmentation: uncover customer behaviors, preferences, and micro-segments by analyzing available customer data in innovative ways 
  • Growth drivers: applying analytical methods to identify sales growth drivers with the potential to help our business units change their marketing strategy to drive business outcomes and sales growth 
  • KPI design: designing smart leading/lagging KPI structures, simplifying the job of marketing and sales teams to readily identify issues or opportunities in their go-to-market activities and campaigns  
  • Investment allocation (ROI): create analytical ROI models that help marketing functions identify the right allocation of resources/investments across brands, marketing channels and campaigns
  • Data science Business Partnering: develop a close understanding of business strategy and market environment, and co-create Data Science solutions with business unit (marketing & sales) leaders that can make a difference to drive business growth (sales)  
  • Analytical process excellence: advance automation of data collection and ETL processes to be used for standard analytic solutions or KPI dashboards to enhance delivery efficiency 


  Next-level advanced priorities:

  • Machine learning: explore the use of Machine Learning and other algorithms to segment, categorize and build predictive models (including sales forecasting) and recommendation engines for answering high priority business needs and enabling adjustments to strategic or tactical decision making
  • Natural language processing: develop a set of toolbox to analyze and mine textual information in Japanese so that such tools can speed up insight generation and be used (as an API) for multiple services internally
  • Data wrangling:  identify opportunities to utilize alternative data sources such as Online Data Mining (Web crawling) and Open Data initiatives and consider how we could use them to better answer business questions or create better models
  • Data visualization: create data visualization tools that enable marketing and sales team members seamlessly grasp the market & customer situation; thus, powering our ambition to become a data-driven marketing & sales organization
  • Business growth: explore new technologies or tools to generate efficiency enhancing business recommendations, e.g. for day-to-day operations of the sales force, predicting target customer potential, channel preferences etc. Guiding principle is to answer the key business questions: “right customer, right channel, right message right timing and right frequency”



  • Collaboration:  collaborate closely and cross-functionally with key Data Science stakeholders locally and globally in DSAA, IT, Analytics Chapter, Tech Squad, IMCM and Business Units to build bridges, a sense of community and enable knowledge sharing
  • Continuous learning:  stay up to date regarding latest developments in data analytics frameworks and solutions by participating in Data Science / advanced analytics / AI related conferences and trainings to understand what latest best practice is. Proactively share what is possible with the analytical functions and business partners to raise awareness among Bayer Japan Data Science community





  • Graduate degree in quantitative field (Statistics, Management Science, Operations Research, Engineering, Finance, Applied Mathematics, Mathematics, Business Administration etc.) 


  Analytical skills

  • Business & data analytics:  Visualization, storytelling and communication to non-technical stakeholders, Excel, KPI and metrics design, intellectual curiosity, integrity
  • Math/statistics: probability, descriptive and inferential statistics, statistical/econometric modeling, Machine learning (classification, regression, clustering, time-series analysis) 
  • Programming languages: Python, R, SQL, Git (plus JIRA for task management)
  • Solution architecture: (ETL) Extract Transform Load, data wrangling and pre-processing, work with remote machines, data bases and data lake infrastructure, knowledge of SQL
  • Visualization: knowledge of Tableau to report and track outcomes in dashboards is a plus


  Collaboration skills & experience

  • Ability to work collaboratively in team-based environments within Japan and with global teams
  • Ability to present and explain complex concepts clearly and visually to a variety of audiences in both Japanese and English
  • Solid track record of working hands-on in a data-analysis related position to deliver insights and actionable recommendations, to guide either human decisions and/or machine-driven outputs
  • Knowledge of pharmaceutical commercial business model and operations is a plus




Please apply for the position through our recruiting website with “Application for Job posting/Bayer in Japan(バイエルグループ ジョブ・ポスティング応募用紙)” in both Japanese and English.社内公募%20応募用紙.docx







Date of Employment: ASAP      
Division: Pharmaceuticals   Location: TOKYO / OSAKA  
Functional Area: Computational Science, Data Science & Statistics   Position Grade: VS1.1 ~ 1.2    
Employment Type: Regular  Work Time: 09:00 - 17:30  
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