Overview
Remote
Depends on Experience
Full Time
No Travel Required
Unable to Provide Sponsorship
Skills
Machine Learning Operations (ML Ops)
Amazon Web Services
PySpark
Job Details
Title: Data Scientist
Location: Remote
Duration: 12 Months Contract to Hire (CTH)
This is a temp-to-hire role. Please ensure the candidate is eligible for permanent hire if required.
The Impact You’ll Make in this Role
As a contractor, you will support the development and maintenance of deep learning models for medical document analysis. You will focus on training, evaluating, and troubleshooting models, processing large text datasets, and running experiments in our AWS environment. You will work with the technical lead to ensure model quality and deliverables, while operating independently in day-to-day execution.
You Will Make an Impact By:
- Training, fine-tuning, and evaluating deep learning models (transformers and related architectures)
- Processing, merging, and analyzing large-scale text datasets
- Troubleshooting model behavior, parameters, and training pipelines
- Running experiments and documenting results
- Deploying models into our AWS-based environment using established tools and workflows
Required Qualifications
- Strong Python skills, especially with PyTorch and Transformers
- Experience training and debugging deep learning models for text
- Solid grounding in statistics, EDA, and machine learning concepts
- Ability to work in AWS and use GitHub-based workflows
- Strong communication and ability to work independently
Preferred Qualifications
- Experience with LLMs, prompt-based methods, or agentic AI
- Familiarity with PySpark or large-scale ETL for textual data
- Experience with experiment tracking and MLOps tools
- Background in healthcare or medical text (nice to have, not required)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.