Time Series Machine Learning Intern

Schneider Electric™ creates connected technologies that reshape industries, transform cities and enrich lives.

Our 153,000+ 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 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 Summer 2025.

The candidate will help in developing data science products based on time series machine learning algorithms using IoT data.

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 time series machine learning algorithms for IoT data, including anomaly detection and classification.



* 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 required.

Prior experience with Python-based libraries for time series, such as SKTime, tsfresh, Ruptures is highly preferred.


* Familiarity with time series machine learning algorithms/ frameworks like ROCKET, Matrix profile techniques, contrastive learning, and 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 commu...