Data Scientist II: Production ML & Data Products

CorVel Corporation; Irvine (CA); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401K

Paid time off

Job summary

CorVel Corporation seeks a Data Scientist to design, build, and deploy ML models and data products that support enterprise initiatives. You will translate business problems into scalable data-driven solutions and work with product managers, engineering, and stakeholders.

You'll develop production-ready models in cloud environments (Azure/AWS), perform feature engineering, model evaluation, and integration into APIs and production systems, while advancing modern AI techniques such as LLMs

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field; Master’s preferred.
• 2-5+ years of experience in data science, ML, or related roles.
• Experience developing and deploying ML models in production environments.
• Experience with cloud-based ML platforms (Azure ML, AWS SageMaker) or similar.

Responsibilities

• Mine and analyze data from internal databases to drive optimization and improvement of product development and business strategies.
• Create new, experimental frameworks to collect data.
• Build tools to automate data collection.
• Develop custom data models and algorithms for data sets.
• Design, build, train, and deploy ML models and data products for enterprise use.
• Translate business needs into scalable data science solutions and modeling approaches.

Skills

Machine learning

Data science

Python

SQL

NLP

LLMs

Azure/AWS

Education

Bachelor's degree in CS/DS/Engineering

Master’s degree preferred

Tools

Azure Machine Learning

AWS SageMaker

APIs

Job description

CorVel Corporation seeks a Data Scientist to design, build, and deploy ML models and data products that support enterprise initiatives. You will translate business problems into scalable data-driven solutions and work with product managers, engineering, and stakeholders.

You'll develop production-ready models in cloud environments (Azure/AWS), perform feature engineering, model evaluation, and integration into APIs and production systems, while advancing modern AI techniques such as LLMs