Senior Data Scientist

Enlyte•UNAVAILABLE, UNAVAILABLE

21d•Remote

About The Position

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. 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).

Requirements

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.

Nice To Haves

Experience with AWS Sagemaker is a plus.

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.