Remote Staff Data Scientist & Tech Lead — Full-Stack ML

Appriss Inc.; Northern (KY); Remote; USD 160,000 - 170,000; Full time

Job summary

Appriss Retail is seeking a Staff Data Scientist / Technical Lead to own the full data science stack, from data engineering to production ML. You will lead a small team, own architecture decisions, and drive strategic AI initiatives across the product.

This is a hybrid, hands-on leadership role with a strong emphasis on delivering scalable data platforms. Ideal candidates have 6+ years in data science/engineering, mastery of SQL and Python, and experience with cloud data platforms and CI/CD for

Qualifications

• 6+ years of experience in data science, data engineering, or a closely related technical discipline.

Responsibilities

• Own end-to-end delivery of high-impact data science projects - from ambiguous business request to production-ready system.
• Design and maintain data pipelines, data models, and governance standards alongside your team; treat infrastructure as a first-class product concern.
• Build, evaluate, and iterate on ML models in production; lead experimentation rigor, monitoring, and lifecycle management.
• Architect and ship LLM-integrated features and agentic workflows - including prompt engineering, tool use, and output evaluation.
• Guide cloud infrastructure architecture for data science projects, taking into account performance, maintenance, and cost criteria.
• Set the standard for code quality: write production-grade Python and SQL, enforce review practices, and maintain documentation.
• Partner closely with engineering to integrate models and pipelines into core product infrastructure.

Skills

SQL

Python

Data pipelines

CI/CD

Cloud platforms

LLM / agent frameworks

IaC (Terraform)

Education

Master's or bachelor's in technical field

Tools

Snowflake

Azure

AWS

GCP

Terraform

Docker

Kubernetes

MLflow

Feature stores

Model registries

Job description

Appriss Retail is seeking a Staff Data Scientist / Technical Lead to own the full data science stack, from data engineering to production ML. You will lead a small team, own architecture decisions, and drive strategic AI initiatives across the product.

This is a hybrid, hands-on leadership role with a strong emphasis on delivering scalable data platforms. Ideal candidates have 6+ years in data science/engineering, mastery of SQL and Python, and experience with cloud data platforms and CI/CD for