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Job Description

Data Scientist

Philip Morris is leading the transformation of our industry with Reduced Risk Products. The intent is to help every smoker to stop or switch to a less harmful alternative. This is our smoke free future mission. As we transform our industry, so we are transforming our business to be more consumer focused, innovative, forward-leaning and agile Why work for us? Here are 3 reasons PMI is the ultimate Employer to unlimit yourself: 1. We’re international: you work with clients and learn on-the-job from team members from all over the world; 2. We’re flexible: your work fits you and not the other way round, thanks to our Flexible Work Arrangement Program; and 3. We’re a certified top employer: we consider our employees to be our strongest asset, and we are developing talent throughout all levels of the organization. Accountabilities: Some of the key responsibilities include: o Building mathematical/statistical models to gain deep insights into market dynamics, movements and opportunities, directly inputting into our strategic decision-making process around promotional activities, program deployment and investments; o Conduct ad hoc deep dives into consumer behavior patterns and experience with IQOS, allowing for continuous improvement and optimization of our CRM segmentation and journeys o Performs regular market analysis and generate impactful insights for commercial and strategy teams, unpacking the complexities and interdependencies of different events and their impact on our key performance measures; o Translating complex statistical interpretations for key stakeholders; o Connecting with data science communities to explore innovative opportunities. Requirements: We don’t just want any Data Scientist, here is our checklist: o Degree in Applied Statistics, Mathematics or any similar field requiring strong data analysis, such as physics, econometrics, engineering, computer sciences, machine learning, algorithms design or process optimization; o The ability to see and construct the business story behind statistical conclusions o Strong data modeling skills and proven examples of delivering time series analysis and forecasting, multivariate analysis (MVA), regression, Support Vector Machines, Bayesian methods etc. o Experience in research, development and deployment of forecasting and optimization capabilities across commercial functions/activities, identifying gaps and opportunities for better commercial investment. o Solid logical reasoning in feature selection, correlation of features, modelling techniques required o Experience in using SQL, Python and/or R; o Familiarity with visual analytics platforms such as PowerBI and Tableau o Knowledge of Hadoop ecosystem, Amazon Web Services o Experience in any of the following would be highly regarded: structural equation modelling for demand estimation, Channel attribution/effectiveness/optimal mix modelling, causal inference, scenario planning with MC simulations If you fit the above requirements, you are the one we need for our Commercial Analytics team.
  • Contract
    Full-Time
  • Location
    Tokyo, Japan
  • Department
    Finance
  • Remaining Openings
    1
  • Job ID
    26696
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