GLOBAL IS / IT DATA PROFESSIONAL - DATA SCIENCE (Nanterre, MA) presso None

Hungry for challenges? Join a group with innovation at its heart and contribute to the automotive revolution!

OPmobility is a world-leading provider of innovative solutions for a unique, safer and more sustainable mobility experience. Innovation-driven since its creation, the Group develops and produces intelligent exterior systems, customized complex modules, lighting systems, clean energy systems and electrification solutions for all mobility companies. With a €11.4 billion economic revenue in 2023, a global network of 152 plants and 40 R&D centers, OPmobility relies on its 40,300 employees to meet the challenges of transforming mobility.

Our ambition? Provide automakers with cutting-edge equipment and solutions to develop tomorrow’s clean and connected car.

The Data Scientist uses its analytical, statistical and programming skills to collect, analyze and interpret large data sets. It is responsible for developing and maintaining data science models to serve digital use cases. It belongs to the Data Center of Excellence, and is detached to domains to work on use-cases in product teams. 

Knowledge / Qualification 

Degree in Mathematics, Applied Mathematics, Computer Science, Engineering or relevant field; Data Science or other quantitative field is preferred 

Previous Experience (If relevant) 

Proven Experience as Data Scientist using a variety of data mining/data analysis methods, data tools to build and implement models. 

Key technical competencies 

• Proficiency in Mathematics, Statistics and Machine Learning 

• Proficiency in Python, R, Spark 

• Knowledge in small- & large-scale database design, maintenance and querying (SQL & nonSQL, Kafka consumers, ElasticSearch...) 

• Cloud services 

• Experience creating and using advanced machine learning algorithms and statistics with open source libraries (ScikitLearn, TensorFlow...): regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.  

• MLOps technologies and experience in moving and maintaining a Machine Learning model in production 

• Data mining, cleaning, collecting & analysis 

• Data visualization 

• Tool building for automation, CI/CD 

Interface 

Use-case users, Data Office, Data Managers, Center of Excellence, IT, plants 
 

Key behavioral competencies (on top of PO Group competencies) 

• Effective communicator 

• Strong analytical skills 

• Problem-solver

Other requirements 

• Strategic understanding on how Data enables business goals 

• Product Management and agile methodologies 

• Understanding of PO’s technological environment 

• Interest in data management 

Missions 

• Support data domains to ideate, design & deliver digital use cases using data science models  
• Maintain models and provide support to data model users 
• Conduct experimentation and contribute to the Data Science community 

Data Science use-case delivery:  

• Contributes to use-case ideation, framing & scoping activities under the lead of a Data Manager. In particular, 

• Identifies data science opportunities lying in the Data Domain 

• Works with the Data Manager and Data Engineer to frame data needs & data quality 

• Works with the Data Manager and possibly a designer or a BI engineer to shape the use-case UX & UI for the user to take best advantage of the models 

• Studies, designs and develops models for analysis, exploitation, prediction and restitution of data 

• Defines data quality controls to ensure model robustness 

• Works closely with data engineers on data models & pipelines 

• Pushes models to production (MLOps) 

Use-case run: 

• Monitors and maintains its models, adopting MLOps best practices, with possible support of IT Operations 

• Provides support to users on Data Manager demand 

• Sets up and implements adoption metrics and ML success metrics 

Innovation & Data Science community 

• Performs data science peer reviews in other projects from any Data Domain 

• Conducts experimentation projects with new models and techniques, sets up demonstrators and POV (Proof of Value) with the business teams 

• Actively participates in the Data Science community to 

• Improve data science processes and tools, e.g., MLOps 

• Share project return of experience 

• Train peers in advanced data science technologies 

• Train the data citizen for self-modeling & statistics 

As a responsible company, OPmobility pays particular attention to diversity and equality within its teams and the Group commits to treat all job applications equally.