Data Science Manager — Full-Stack ML & Production Systems

Appriss Inc.; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Medical plans

Dental and vision

Health savings account

Parental leave

401(k) with company match

Disability insurance

Wellbeing resources

Learning & development

Job summary

Appriss Retail seeks a Data Science Manager to lead a small, high-output team while staying hands-on. You’ll own data science end-to-end — data engineering, governance, and production model delivery — not just modeling. You’ll write code, review pipelines, and drive architectural decisions, while growing your team around you.

This full-stack role requires crafting data contracts, guiding infra, and collaborating with product/engineering to deploy real-world AI solutions at scale.

Qualifications

• 6+ years of experience in data science, data engineering, or closely related technical discipline.
• 1+ year of direct people management or formal technical lead experience over a team.
• Expert-level SQL and Python; production code, not just analysis scripts.
• Deep understanding of data infrastructure: pipelines, warehousing, data modeling, and source system behavior.
• Strong software engineering practices: version control, code review, testing, and has built or maintained a CI/CD pipeline for a data or ML workload.
• 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).
• Has made and defended a build-vs-buy or cost/latency tradeoff on a production ML or data system.
• 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, considering performance, maintenance, and cost.
• Set the standard for code quality: write production-grade Python and SQL, enforce review practices, and maintain documentation.
• Partner with engineering to integrate models and pipelines into core product infrastructure.

Skills

SQL

Python

Data pipelines

Model evaluation

Technical leadership

Communication

Education

Master’s degree or Bachelor’s Degree in a technical, quantitative field

Tools

Snowflake

Azure

AWS

GCP

Terraform

Docker

Kubernetes

CI/CD

MLflow

Airflow

dbt

Job description

Appriss Retail seeks a Data Science Manager to lead a small, high-output team while staying hands-on. You’ll own data science end-to-end — data engineering, governance, and production model delivery — not just modeling. You’ll write code, review pipelines, and drive architectural decisions, while growing your team around you.

This full-stack role requires crafting data contracts, guiding infra, and collaborating with product/engineering to deploy real-world AI solutions at scale.