Quality Data Scientist

at  Michelin

Quality Data Scientist
Michelin is hiring!

The Opportunity:
Michelin PRIME is growing and expanding our team! Here at PRIME, we manufacture tires for some of the highest profile vehicles on the market today. We are looking for a data scientist to help build and test innovative data and AI based products to unleash opportunities to detect failures or predict them real time as they occur.

What you will do:

• Understand and work to meet current demands from our customers, i.e. to provide a way to predict machine failures before they occur.
• Support, using data analytics, with a visualization of the result. This work will support the building our data services of tomorrow.
• Develop tomorrow’s data products. This starts with R&D, which will require Artificial Intelligence and Machine Learning skills.
• Fit and evaluate Machine Learning/Advanced Analytics/Advanced Statistics models to address the business problem and satisfy acceptance criteria.
• Present the results and the model (performances and limits) to collaborators and lead technical discussions for model improvement.

What you will bring:

Research Experience

• Ability to keenly understand and diagnose customer difficulties and identify how to address customer problems using existing data and services.
• Using existing services and models, analyze results and conduct research on customer use cases to meet and anticipate customer needs.
• Proficiency in Python, SQL to conduct analysis and perform statistical modeling.
• Analyze and valorize, heterogeneous, possibly unstructured, data masses to extract useful knowledge for the optimization of the company’s offers, services, or processes and to acquire reliable results.

Communication and Decision Support Expertise

• Extract and translate machine data into usable information.
• Analyze results, identify trends and/or ideas for action and makes recommendations based on the analysis of data collected.
• Popularize and present results to decision makers in a format that is accessible to all through data visualization tools.

Qualifications

• Bachelor’s Degree or higher in Statistics, Applied Mathematics, Computer Science Information Systems or equivalent
• Must have experience with data science methodology and techniques: Exploratory Data Analysis, Feature Engineering,
• Cross Validation, Visualization, Advanced Analytics, Machine Learning, Predictive Modeling
• Relevant software development skills with Python (PySpark) with proficiency using Azure Service,
• Exposure/experience with productionizing models with MLOps: CI/CD workflows with a Product mindset
• Collaborates and work within an international team environment.

Inspire Motion for Life: Apply Today!
As the leading mobility company, we work with tires, around tires and beyond tires to enable Motion for Life. Dedicated to enhancing our clients’ mobility and sustainability, Michelin designs and distributes the most suitable tires, services and solutions for our customers’ needs. Michelin provides digital services, maps and guides to help enrich trips and travels and make them unique experiences. Bringing our expertise to new markets, we invest in high-technology materials, 3D printing and hydrogen, to serve a wide a variety of industries—from aerospace to biotech. Headquartered in Greenville, South Carolina, Michelin North America has approximately 23,000 employees and operates 34 production facilities in the United States and Canada.
MICHELIN® tires have been ranked the #1 Tire Brand across major categories and segments by industry experts and consumers alike. For nearly three decades we’ve been recognized for our achievements in Customer Satisfaction, Performance, Durability, Technology and Innovation.
Michelin cares for the personal and professional development of its employees. We support career advancement through various options, which include: skill and career development, training, career exploration and work with cross-functional teams. We offer the possibility of a varied and fulfilling career path in an environment where unique contributions are valued.
Michelin offers 10 Business Resource Groups (BRGs) which are all-inclusive groups created and led by employees who have shared life experiences across various diversity dimensions. Each group supports business strategies and initiatives along with meeting the needs of members. The goal of each group is to help employees feel welcome and included, support employee engagement and encourage professional development. BRGs also provide cross-cultural support, career management resources and opportunities for community involvement.
Michelin provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), political affiliation, military service, or other non-merit-based factors. Consistent with these obligations, Michelin also provides reasonable accommodations to employees and applicants with disabilities and for sincerely held religious beliefs. If you need accommodation for any part of the employment process because of a disability, please contact us at
accommodations@michelin.com
.
This position is not available for immigration sponsorship.
Get in the driver’s seat and be on your way to a meaningful professional journey

• Understand and work to meet current demands from our customers, i.e. to provide a way to predict machine failures before they occur.
• Support, using data analytics, with a visualization of the result. This work will support the building our data services of tomorrow.
• Develop tomorrow’s data products. This starts with R&D, which will require Artificial Intelligence and Machine Learning skills.
• Fit and evaluate Machine Learning/Advanced Analytics/Advanced Statistics models to address the business problem and satisfy acceptance criteria.
• Present the results and the model (performances and limits) to collaborators and lead technical discussions for model improvement