Manufacturing Data Science Internship (Masters or PhD, Summer 2023)

 

Seagate Technology is reshaping the Datasphere through advanced data storage and data generation technology development. We help maximize humanity’s potential by delivering world-class, precision engineered data solutions developed through sustainable and profitable partnerships.

Do you enjoy solving real-world data challenges with advanced technology? Are you passionate about asking questions and analyzing data to deepen knowledge and understanding? Are you excited about developing robust Industry 4.0 manufacturing systems?

Seagate Technology’s advanced manufacturing HDD mechanical development team is looking for an experienced, passionate, and talented Data Scientist with Data Engineering experience to innovate in the rapidly growing area of Industry 4.0 and Big Data. Seagate’s recording head factories manufacture an excess of three million heads per day. This team develops the data analytics that define manufacturing success. This role will be located Bloomington, MN.

 

· Develop scalable tools leveraging computer vision and machine learning to solve real-world problems in areas such as Image Defect Detection, Sensor Anomaly Detection, and Time Series prediction.

· Work closely with other data scientists and engineers to scale-up data solutions across diverse manufacturing applications.

· Lead your own project. Suggest, collect, and synthesize requirements. Create an effective roadmap towards the deployment of a production-level analytics applications.

· Independently perform Data Science tasks (including data exploration, cleaning, factor generation/selection, and data visualization) to support large-scale Data Science initiatives in our global team.

· Stay current with the latest research and technology and communicate your knowledge throughout the enterprise.

 

· MS or PhD in a quantitative discipline, e.g. Engineering, Computer Science, Mathematics, Statistics, Operations Research, or Data Science

· Knowledge and hands-on experience with machine learning techniques and statistical concepts (Statistical tests , Supervised and Unsupervised learning techniques used for clustering, classification, regression . . . )

· Knowledge and hands-on experience with computer vision

· Strong ability to develop and debug in Python. Java, C or C++, and Matlab are also relevant.

· Strong experience with machine learning APIs and computational packages (TensorFlow, PyTorch, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels).

· Experience with container orchestration and cluster management systems (docker, kubernetes)

· Familiarity with basic data table operations (SQL, Hive, etc.)

· Experience with time-series statistical and machine learning modeling: ARIMA, VAR, LightGBM, etc.

· Experience in Deep Learning: DNN, CNN, RNN, GAN or other auto encoder (AE), etc.

· Experience with Version Control Systems (GIT)

· Ability to work both individually and collaboratively in teams to achieve project goals

· Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences

 

· Experience developing computer vision and deep learning models for image defect detection

· Experience developing advanced time-series prediction and forecasting models

· Experience scaling machine learning modeling system tools to high volume centralized systems