Staff Data Scientist / Technical Lead (Full-Stack / Production ML)

Location: Remote - United States. Travel required up to 10% for training and conferences.

Company

Retail loss prevention products unify data across stores, online channels, and customer service to reduce returns, shrink, and incident-management costs.

What you will do

• Own end-to-end delivery of data science projects from ambiguous business requests through production-ready systems.
• Design and maintain data pipelines, data models, governance standards, and cloud infrastructure for data science workloads.
• Build, evaluate, monitor, and manage the lifecycle of production machine learning models.
• Architect and ship LLM-integrated features and agentic workflows involving prompt engineering, tool use, and output evaluation.
• Set technical direction for a small data science team, establish code-quality and review standards, and mentor team members.
• Partner with product, engineering, and business stakeholders to define analytical work, roadmap priorities, and success criteria.

Requirements

• 6+ years of experience in data science, data engineering, or a closely related technical discipline.
• At least 1 year of formal technical leadership experience with readiness to grow into direct management.
• Expert-level Python and SQL, with experience writing production code.
• Strong knowledge of data pipelines, warehousing, data modeling, source systems, version control, code review, testing, and CI/CD.
• Experience with Snowflake and a cloud platform such as Azure, AWS, or GCP, plus infrastructure-as-code and containerization.
• Master's or bachelor's degree in a technical or quantitative field.

Nice to have

• Experience with dbt, Airflow, Spark, or equivalent modern data-stack tools.
• LLM experience including prompt engineering, RAG, fine-tuning, or agent frameworks such as LangChain or LlamaIndex.
• Experience with agentic AI architectures involving multi-step reasoning, tool use, memory, and orchestration.
• Experience in retail, fraud detection, or transaction-level data at scale.

Culture & Benefits

• Medical, dental, and vision plan options, plus health savings and flexible spending accounts.
• Paid parental leave, generous paid time off, life coverage, and short- and long-term disability coverage.
• 401(k) with immediate vesting and company match.
• Health and wellbeing resources, including Calm and Sworkit.
• Learning and development opportunities.
• Eligible for a 12-15% bonus in addition to base salary.

Hiring process

• Technical deep dive focused on modeling skills.
• System design discussion covering model or pipeline architecture, deployment, operations, infrastructure, and cost tradeoffs.