Staff Data Scientist & Technical Lead - Production ML

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

Benefits offered by this job

Bonus up to 15%

Remote work (US)

Comprehensive benefits

Job summary

Appriss Retail seeks a Staff Data Scientist / Technical Lead to own the full data science stack, from data engineering and governance to production ML delivery. You will shape architecture for data platforms, ML systems, and agentic workflows in a hands-on leadership role.

The role requires building real data platforms, shipping models to production, and guiding cloud infra with cost-aware decisions. Remote within the United States, with responsibilities spanning analytics and product impact.

Qualifications

• 6+ years of experience in data science, data engineering, or a closely related technical discipline.
• 1+ year of formal technical lead experience over a team with the readiness and interest to grow into direct management.
• Expert-level SQL and Python; production code, not just analysis scripts.
• Cloud data platform experience: Snowflake, Azure (preferred), AWS, or GCP.
• Working knowledge of infrastructure-as-code (Terraform, CloudFormation, or equivalent) and containerization (Docker, and ideally Kubernetes or a managed container service).
• Familiarity with ML platform tooling: MLflow, feature stores, model registries, or similar.

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

CI/CD

Data modeling

Data pipelines

Education

Master's degree

Bachelor's degree

Tools

Snowflake

Azure

AWS

GCP

Terraform

CloudFormation

Docker

Kubernetes

MLflow

LangChain

LlamaIndex

Job description

Appriss Retail seeks a Staff Data Scientist / Technical Lead to own the full data science stack, from data engineering and governance to production ML delivery. You will shape architecture for data platforms, ML systems, and agentic workflows in a hands-on leadership role.

The role requires building real data platforms, shipping models to production, and guiding cloud infra with cost-aware decisions. Remote within the United States, with responsibilities spanning analytics and product impact.