· We are looking for a Data Scientist who supports us on our mission to develop our E2E Advanced analytics products and be the link between the Global Supply Chain analytics team and the Customer Health Care (CHC) Global Supply Chain Transformational program
· As lead of the transformation program within the Global SC analytics team, he/she will support the roll outs and monitor all project activities (design, build, test, correction, analysis..)
· Creating valuable, transformative business strategies through measurement, manipulation, reporting and dissemination of broad sets of data.
· Applying and advising on state-of-the-art advanced analytic and quantitative tools and modeling techniques in order to derive business insights, solve complex business problems and improve decisions.
· Working with a wide range of stakeholders and functional teams.
· Having passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
· Develop advanced models in Python and/or R to tackle a high variety of problems.
· Contribute to the development of the end-to-end Machine Learning pipeline in a cloud infrastructure (data management, model deployment, industrialization).
· Engage with some of our clients to understand their business challenges and tailor the algorithms to their needs.
· Be the Global SC transformation program focal points for any topics related to Data Analytics
· Ensure that the connection to the data lake covered all Customer Health Care (CHC) needs
· Ensure the new set up of the Dataset is correctly integrated and matching with Customer health care Business unit during the cutover phase.
· Make any readjustment and modification needed post Cutover phase in Analytic Tools dedicated to Customer Health Care (CHC) data
· Manage the different Criteria of the Master Data specific to Customer Health Care (CHC) division
· S&OP automatic process: adapt according to CHC needs the S&OP template and extraction through R (ex: Regional S&OP template)
· Data Analysis – concerning all Master Data Topics
Required skills & experience
· Advanced degree in a quantitative field, such as computer science, engineering, physics, statistics or applied mathematics.
· Lead the interaction between the data science team and business stakeholders.
· Deep understanding of fundamental machine-learning principles.
· Data management skills: SQL, data pipelines, etc.
· Advanced knowledge of machine-learning technologies and tools, such as big data stack, Python, R and visualization techniques.
· Ability to break down complex information into relevant and digestible points.
· Team-player attitude to drive the end-to-end implementation of use cases under time pressure.
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