641 IT & Software Developer jobs in the US

Pear Care jobs

Data Science and Machine Learning Internship

$41,500 - 53,500
Pear Care
Ward Avenue 404, Remote + Remote (US)
$41,500 - 53,500
Company Size icon
Company Size
<50
Company Type icon
Company Type
Product
Exp Level icon
Exp Level
Junior
Job Type icon
Job Type
Internship
Language icon
Language
English
Visa sponsorship icon
Visa sponsorship
No

Requirements

Must:
- Experience with Python and data libraries such as Pandas - Familiarity with or willingness to learn about PySpark and large-scale data processing - Exposure to PyTorch or other machine learning frameworks - Comfort working in a Linux/cloud environment; AWS experience is a plus - Curiosity, strong problem-solving abilities, and a passion for learning - Interest in healthcare, data, and developing technology that benefits individuals

Technologies

Machine Learning
PyTorch
PySpark
pandas

Responsibilities

- Construct and evaluate machine learning models to analyze and compare healthcare providers - Manage large-scale datasets using AWS, PySpark, and Pandas - Design and implement data pipelines for data ingestion, cleaning, and transformation - Prototype and train models utilizing PyTorch - Collaborate with engineers and product teams to convert models into production features - Examine data to identify patterns, trends, and actionable insights for patients - Document your progress and present findings to both technical and non-technical colleagues

Description


At Pear Care, we are committed to helping patients make informed healthcare choices through data analysis. We believe that transparency and intelligent assessment can significantly enhance patient outcomes. As a Data Science / Machine Learning Intern, you will gain practical experience with real-world data, robust tools, and a chance to make a meaningful impact. Our team offers a supportive environment where you can grow as a data scientist or ML engineer, contributing to a product that genuinely matters. Enjoy benefits such as a flexible schedule and professional development support while working remotely.
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