A fast-growing consumer products company in Los Angeles, CA is seeking a Full-Stack Data Scientist / ML Engineer to own internal data infrastructure, AI automation, knowledge systems, and workflow optimization. This role will continue and expand the work of our current AI/data lead and will have direct impact across operations, sales, customer support, and product development.
This is a high-visibility, high-autonomy position reporting directly to the CEO.
What You'll Do
AI & Automation (Primary Focus)
- Build and maintain internal AI agents that support quoting, product lookup, workflow automation, and exception handling.
- Develop NLP systems to automatically parse customer inquiries, classify account types, and identify action routing.
- Maintain and grow an internal LLM-powered knowledge base that captures business rules, supplier constraints, SKU attributes, and operational exceptions.
Data Engineering & ETL Pipelines
- Design and own production-grade ETL pipelines across CRM, accounting, supplier data, SKU catalogs, and operational datasets.
- Build reliable data models that unify siloed systems, enabling high-quality analytics and automation.
- Implement automated data-cleaning processes that support daily operations and decision-making.
Internal Tools & Script Development
- Develop Python tools and micro-automations for pricing logic, invoice workflows, sample handling, customer communication, and data synchronization.
- Create internal dashboards, utilities, and command-line workflows that support sales, operations, and leadership.
- Serve as the primary builder of internal automation infrastructure.
Operations & Process Analytics
- Analyze operational bottlenecks and performance trends across production timelines, shipping, and customer response cycles.
- Provide insights that directly improve efficiency, speed, and customer experience.
Cross-Functional Collaboration
- Work closely with leadership and operations teams to identify automation opportunities.
- Translate evolving, fast-paced business rules into robust data logic and system behavior.
- Document internal processes and maintain reliable technical infrastructure.
What We're Looking For
Required
- 36+ years in Data Science, ML Engineering, or a full-stack data role
- Strong Python engineering fundamentals (Pandas, NumPy, scikit-learn, async workflows)
- Hands-on experience with LLM systems (embeddings, retrieval, fine-tuning, structured prompting, agent-style workflows)
- Experience building and maintaining ETL pipelines from multiple SaaS systems and CSV/Excel sources
- Experience integrating with CRM and accounting APIs (HubSpot, QuickBooks, or comparable platforms)
- Strong SQL skills and experience designing logical data models
- Demonstrated ability to build internal automation tools or operational scripts
- Excellent written communication and documentation skills
Nice to Have
- Experience with workflow orchestration tools (Airflow, Prefect, Make, Zapier)
- Experience with OpenAI, Anthropic, or similar LLM ecosystems
- Experience building retrieval systems or internal knowledge bases
- Background in e-commerce, wholesale, or operations-heavy environments
What This Role Offers
- Ownership of the entire data and AI automation ecosystem
- A chance to build from scratch: pipelines, agents, tooling, and internal intelligence systems
- Direct work with executive leadership and major influence on company operations
- The ability to dramatically reduce manual workload across teams through automation
- A high-impact role where your work is used daily across the organization
