Lead Data Scientist: MLOps & AI Strategy

Relha LLC; Springdale, Northern (AR, KY); Hybrid; USD 140,000 - 180,000; Full time

Benefits offered by this job

Paid time off

401(k) plans

Affordable health, life, dental,vision

Job summary

Tyson Foods, Inc. in Springdale, AR seeks a Lead Data Scientist to develop and implement analytics apps that transform raw data into actionable insights, with end-to-end testing, deployment smoke tests, and continuous monitoring.

You will co-own the MLOps roadmap and mentor teams on AI strategy and model evaluation. The role emphasizes scalable model deployment, cost efficiency, observability, and data science lifecycle governance, involving architecture patterns and reusable ML components in

Qualifications

• Bachelor's or equivalent in CS/Math/Stats; 3 years’ related experience (2 years for Master’s).
• Experience in ML with Scikit-Learn and TensorFlow.
• Experience in unstructured data ingestion and staging.
• Design and deployment of scalable RESTful services exposing ML models.
• Computer vision with advanced image processing and object segmentation.
• Distributed systems with messaging queues for async processing.
• Docker and Git for containerization and lifecycle management.

Responsibilities

• Co-own the MLOps roadmap and mentor teams on AI strategy and model evaluation/validation.
• Scale model deployment with emphasis on performance, cost, and observability.
• Develop end-to-end testing, integration and smoke testing in ML pipelines.
• Broaden data science lifecycle governance with roadmaps tied to business outcomes.
• Contribute to reusable ML architecture patterns.

Skills

Machine Learning

Data Engineering

RESTful APIs

Computer Vision

Distributed Systems

Education

Bachelor's or Master’s in Computer Science, Mathematics, Statistics or related field

Tools

Docker

Git

Job description

Tyson Foods, Inc. in Springdale, AR seeks a Lead Data Scientist to develop and implement analytics apps that transform raw data into actionable insights, with end-to-end testing, deployment smoke tests, and continuous monitoring.

You will co-own the MLOps roadmap and mentor teams on AI strategy and model evaluation. The role emphasizes scalable model deployment, cost efficiency, observability, and data science lifecycle governance, involving architecture patterns and reusable ML components in