Junior Data Scientist

Enlyte•UNAVAILABLE, UNAVAILABLE

4d•Remote

About The Position

This is a full-time remote position that can be located anywhere in the U.S. Mitchell is looking for a Data Scientist to identify and deliver AI/ML opportunities across our product portfolio. You'll work closely with product managers and engineers to turn business problems into working solutions — including generative AI and large language models (LLMs).

Requirements

Strong analytical skills and solid knowledge of ML methodologies, data engineering, and feature engineering.
Ability to collaborate with engineering teams on scalable ML pipelines and established standards.
Clear communication skills — comfortable presenting to non-technical stakeholders and sharing knowledge across teams.
A habit of staying current with ML research through papers, blogs, and open-source projects.
MS or PhD in Math, Statistics, Computer Science, or a related field.
MS: 2 years of professional ML experience
PhD: 1+ years of professional ML experience
2+ years of experience building, deploying, and maintaining ML models in production.
Hands-on experience with data warehouses, feature engineering, ML pipeline automation, and model monitoring.
Solid knowledge of ML algorithms and techniques, with the ability to explain core concepts clearly.
High proficiency in Python and SQL.
Good understanding of data warehousing and ETL processes.
Strong written and verbal communication skills.

Nice To Haves

Experience with AWS SageMaker.

Responsibilities

Identify AI/ML opportunities across products and support implementation efforts.
Design and test prompts for LLM-based generative AI features.
Build, evaluate, and deploy machine learning models in production.
Partner with product managers, engineers, and domain experts to solve business problems with ML.
Follow and contribute to best practices for ML pipelines, model monitoring, and deployment.
Present findings clearly to both technical and non-technical audiences.