Job Title

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 DoAI & 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 ForRequired- 3–6+ 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 skillsNice 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 environmentsWhat 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