Data AI SCIENTIST

Stellantis
Auburn Hills, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Auburn Hills, United States of America

Tech stack

API
Artificial Intelligence
Data analysis
Artificial Neural Networks
Computer Vision
Big Data
Decision Tree Learning
Cluster Analysis
Computer Programming
Information Engineering
Data Mining
Statistical Hypothesis Testing
Python
Machine Learning
Natural Language Processing
TensorFlow
PyTorch
Snowflake
Spark
Deep Learning
Information Technology
Data Analytics
Databricks

Job description

The candidate will be responsible for developing advanced data use cases in Stellantis Global Supply Chain business domain, leveraging 360 ecosystem (Supply Chain, Manufacturing, Engineering, Sales and Marketing, and Purchasing. The candidate will work in a very diverse, international and challenging environment, in close collaboration with business stakeholders and data engineering teams. The candidate will have strong experience in building and implementing models, using/creating algorithms and creating/running simulations. As well as using a variety of data mining/data analysis methods., Merge large, complex data sets that meet business requirements Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Writing and refactoring the code into reusable libraries and API Support business analytics initiatives across SC departments Facilitate the internal and external data science & AI network Be a specialist on specific data science fields (e.g. NLP, Computer Vision, Time Series), Merge large, complex data sets that meet business requirements Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Writing and refactoring the code into reusable libraries and API Support business analytics initiatives across SC departments Facilitate the internal and external data science & AI network Be a specialist on specific data science fields (e.g. NLP, Computer Vision, Time Series) At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future.

Requirements

Master in Data Science / Computer Science 5 years of relevant experience (i.e. ICT and/or Supply Chain) Knowledge of at least one of some of the main Big Data frameworks and platforms: Spark, Databricks, Snowflake Strong programming skills in Python and SQL Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, ...) Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, ...) and their real-world advantages/drawbacks Combination of business focus, analytical and problem-solving skills to quickly define a data-driven solution within different initiatives Ability to work within a team and with a proactive attitude Preferred Qualifications: PhD Experience in a multinational (global) work environment AI: mastery in one AI field such as Natural Language Processing or Computer Vision is appreciated Palantir Foundry platform Microsoft PowerBI / Fabrics tool (incl. DAX programming language) Deep learning frameworks (Pytorch, Tensorflow, ...) Ability to communicate and summarize technical topics for non-technical audience (incl. leadership) The candidate will be responsible for developing advanced data use cases in Stellantis Global Supply Chain business domain, leveraging 360 ecosystem (Supply Chain, Manufacturing, Engineering, Sales and Marketing, and Purchasing. The candidate will work in a very diverse, international and challenging environment, in close collaboration with business stakeholders and data engineering teams. The candidate will have strong experience in building and implementing models, using/creating algorithms and creating/running simulations. As well as using a variety of data mining/data analysis methods.

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