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Data Scientist Group Leader - Competency Research Labs/Materials Technology - Job Opening ID: 570417

Saint-Gobain’s North American R&D center is looking for a data scientist to lead its data analytics team.


The data analytics team of Saint-Gobain’s North American R&D center supports the different businesses of the company in their efforts related to new product development, business intelligence improvement (CRM data, supply chain, logistics) and manufacturing processes transition toward smart manufacturing. The team works with cloud IaaS and PaaS (Apache Hadoop Platform) provided by Saint-Gobain central services or businesses.

The main responsibilities include:

  • Leading meetings with internal customers to identify data analytics needs and scope projects including small scale statistical analyses, big data discovery projects and production deployments.
  • Establishing project strategy in collaboration with team members (data scientist, data engineer). This includes defining the data architecture and the requirements in terms of data format and structure, and identifying the relevant statistical and machine learning tools and techniques.
  • Assigning projects to self or team members and ensuring that projects are successfully conducted using a standard project management approach.
  • Cleaning and manipulating data, and employing sophisticated analytics programs, machine learning and statistical methods to generate valuable insight.
  • Presenting results from rigorous technical analyses in a clear and actionable way to project stakeholders and management.
  • Summarizing project approach and results in concise and accurate technical memos.
  • Being an active support to the development of data analytics within Saint-Gobain through completion of successful projects with a measurable added value, sharing of results with a large audience, being an active member of Saint-Gobain worldwide data analytics community (participation in tech days, sharing of best practices).
  • Elaborating team strategy and ensuring strategy implementation.
  • Developing direct reports and holding direct reports and projects teams accountable (progress, budget, timeline, deliverables).
  • Leading own group as well as cross functional teams by managing self and others to execute and deliver project objectives.


  • Demonstrated technical excellence in statistics, and data analytics (data processing, design of experiments, inferential statistics, regression analysis, statistical modeling, supervised machine learning).
  • Demonstrated experience with the production of machine learning algorithms on Hadoop clusters.
  • Demonstrated experience with the following applications/languages: Spark, Hive, Impala, Solr, HDFS, NoSQL, Python, R, Matlab, SAS.
  • Familiarity with the following data engineering applications: Kafka, Oozie, and at least one ETL/ELT tools.
  • Ability and desire to self-learn and pick up emerging technologies.
  • Strong team player and creative thinking skills, and a desire to "make a difference".
  • Ability to develop relationships with others and to fluently translate technical findings to a non-data science oriented team (manufacturing, marketing, sales, supply chain).
  • Ability to efficiently communicate orally and by email with people having a wide variety of background.
  • Demonstrated ability to write concise and accurate technical documents and give strong technical presentations to a wide variety of audience.
  • Demonstrated ability to maintain composure and organize teams in high pressure situations.
  • Demonstrated ability to give and receive constructive feedback and coach direct reports. Demonstrated ability to flex style to match needs of direct reports (possesses more than one way to communicate to get things done).
  • Familiarity with smart manufacturing concepts and related data architecture is a plus.
  • Familiarity with smart manufacturing-oriented SCADA systems such as Ignition is a plus.
  • Familiarity with Docker container technology is a plus.
  • Familiarity with Microsoft Azure technology is a plus.


  • Master’s degree in Computer Science, Applied Mathematics, Mathematics/statistics, Econometrics and 10+ years of industrial experience, or PhD in similar fields with 6+ years of industrial experience. A Bachelor’s degree in Engineering is a plus.
  • 2+ years of industrial experience managing direct reports
  • 3+ years of industrial experience as a data scientist