Description

At Enlyte, we combine innovative technology, clinical expertise, and human compassion to help people recover after workplace injuries or auto accidents. We support their journey back to health and wellness through our industry-leading solutions and services. Whether you're supporting a Fortune 500 client or a local business, developing cutting-edge technology, or providing clinical services you'll work alongside dedicated professionals who share your commitment to excellence and make a meaningful impact. Join us in fueling our mission to protect dreams and restore lives, while building your career in an environment that values collaboration, innovation, and personal growth.

Be part of a team that makes a real difference.

Mitchell, an Enlyte company, is seeking an experienced Data Scientist to help us discover opportunities to drive customer and business value by leveraging AI/ML technology including generative AI and large language models, and guide product managers and engineers to realize the solutions within our broad range of products.

Responsibilities:

• Drive discovery of AI/ML opportunities across product portfolio and guide implementation.
• Design and optimize prompts for large language models to support generative AI features.
• Build, evaluate, and deploy machine learning models in production environments.
• Collaborate with product managers, engineers, and domain experts to translate business problems into technical solutions.
• Define best practices for ML pipeline automation, model monitoring, and scalable deployment.
• Communicate findings and recommendations to technical and non-technical stakeholders.

The successful candidate will be a self-starter, capable of driving the discovery process to tackle ambiguous problems alongside subject matter experts across business functions with minimal direction.  This candidate will:

• Have excellent analytical skills and in-depth knowledge of machine learning methodologies, data and feature engineering.
• Be capable of providing insights to the engineering team in building scalable ML pipeline automation and defining best practices.
• Be an excellent communicator, capable of presenting findings to non-technical audiences and enjoy giving talks to expand the overall AI/ML knowledge of our organization.
• Demonstrate commitment to staying current with the latest research (through papers, public codebases, and blogs).

• MS/PhD in appropriate field (e.g. Math/Statistics/Computer Science) with 6+ (MS) / 3+ (PhD) years of professional experience in machine learning projects.
• 1+ years of experience in building, deploying and maintaining machine learning models on production environment.
• Experience in machine learning projects involving data warehouse, feature engineering, ML pipeline automation and ML monitoring.
• Excellent understanding of many machine learning algorithms/techniques/tools, capable of explaining the underlying concepts and principles.
• High proficiency with Python programming language.
• High proficiency with SQL.
• Good understanding of data warehousing and ETL techniques.
• Excellent written and verbal communication skills with the ability to educate and influence.
• High level of initiative and passion to deliver results.
• Experience with AWS Sagemaker is a plus.

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