Schneider Electric™ creates connected technologies that reshape industries, transform cities and enrich lives. Our 144,000 employees thrive in more than 100 countries. From the simplest of switches to complex operational systems, our technology, software and services improve the way our customers manage and automate their operations. Help us deliver solutions that ensure Life Is On everywhere, for everyone and at every moment: https://youtu.be/dux6kG13QWM

Great people make Schneider Electric a great company.

Based in Andover, MA, Schneider Electric's Artificial Intelligence (AI) hub's offer management team aims to deliver world class AI products to solve customer challenges by enhancing digital offers with AI driven insights and new kinds of AI products addressing Energy, Sustainability and Industrial Automation domains, all leveraging a comprehensive Platform approach.

We're looking for a passionate and product-minded Data Science intern to join us in the summer of 2024.

The candidate will help in developing data science products based on time series machine learning algorithms using IoT data. The goal of these products is to accelerate the offer development lifecycle by enabling repeatable and performant data science workflows.

The position will report to the Senior Principal ML/AI Architect in the team but will work closely with respective offer managers and usecase squads.

Responsibilities

• Develop Python-based technical products based on time series machine learning algorithms for IoT data


• Create frameworks for prototyping and benchmarking machine learning algorithms and tools on standardized datasets


• Select appropriate datasets and data representation methods


• Run machine learning tests and experiments to support the product development


• Develop and test strategies for training and retraining machine learning systems


• Research and survey industrial reports and technical papers on latest industrial trends, case studies, models and methodologies.

• The candidate must be currently enrolled in a masters or doctoral graduate program in a related discipline such as Mathematics, Statistics, Physics, Engineering, Data Science or CS


• Demonstrable experience in full stack data science, including developing and deploying machine learning models in a production environment


• Experience working with time series data is preferred. Prior experience with Python-based libraries for time series, such as tsfresh, sktime, Darts and Prophet, and deep learning architectures like InceptionTime and other 1D Convolutional Neural Networks will be a plus!


• Experience exploring and training models with big datasets, using cloud technologies (Kubernetes, AWS, GCP, Azure)


• Proficient in scientific Python (NumPy, SciPy, scikit-learn, Pandas, XGBoost), SQL, and version control (GitHub)


• Ability to formulate hypotheses, draw conclusions and deliver results


• Excellent verbal and written communication and interpersonal skills


• Ability to present findings to stakeholders and communicate results to all colleagues

Let us learn about you! Apply today.

Why us?

Schneider Electric is leading the digital transformation of energy management and automation. Our technologies enable the world to use energy in a safe, efficient and sustainable manner. We strive to promote a global economy that is both ecologically viable and highly productive.

€25.7bn global revenue

137 000+ employees in 100+ countries

45% of revenue from IoT

5% of revenue devoted for R&D

You must submit an online application to be considered for any position with us. This position will be posted until filled

It is the policy of Schneider Electric to provide equal employment and advancement opportunities in the areas of recruiting, hiring, training, transferring, and promoting all qualified individuals regardless of race, religion, color, gender, disability, national origin, ancestry, age, military status, sexual orientation, marital status, or any other legally protected characteristic or conduct. Concerning agencies: Schneider Electric does not accept unsolicited resumes and will not be responsible for fees related to such.Schneider Electric™ creates connected technologies that reshape industries, transform cities and enrich lives. Our 144,000 employees thrive in more than 100 countries. From the simplest of switches to complex operational systems, our technology, software and services improve the way our customers manage and automate their operations. Help us deliver solutions that ensure Life Is On everywhere, for everyone and at every moment: https://youtu.be/dux6kG13QWM

Great people make Schneider Electric a great company.

Based in Andover, MA, Schneider Electric's Artificial Intelligence (AI) hub's offer management team aims to deliver world class AI products to solve customer challenges by enhancing digital offers with AI driven insights and new kinds of AI products addressing Energy, Sustainability and Industrial Automation domains, all leveraging a comprehensive Platform approach.

We're looking for a passionate and product-minded Data Science intern to join us in the summer of 2024.

The candidate will help in developing data science products based on time series machine learning algorithms using IoT data. The goal of these products is to accelerate the offer development lifecycle by enabling repeatable and performant data science workflows.

The position will report to the Senior Principal ML/AI Architect in the team but will work closely with respective offer managers and usecase squads.

Responsibilities

• Develop Python-based technical products based on time series machine learning algorithms for IoT data


• Create frameworks for prototyping and benchmarking machine learning algorithms and tools on standardized datasets


• Select appropriate datasets and data representation methods


• Run machine learning tests and experiments to support the product development


• Develop and test strategies for training and retraining machine learning systems


• Research and survey industrial reports and technical papers on latest industrial trends, case studies, models and methodologies.