Full-Stack Data Scientist

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 PipelinesDesign 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 DevelopmentDevelop 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 AnalyticsAnalyze 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 CollaborationWork 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 ForRequired3–6+ years in Data Science, ML Engineering, or a full-stack data roleStrong 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 sourcesExperience integrating with CRM and accounting APIs (HubSpot, QuickBooks, or comparable platforms)Strong SQL skills and experience designing logical data modelsDemonstrated ability to build internal automation tools or operational scriptsExcellent written communication and documentation skillsNice to HaveExperience with workflow orchestration tools (Airflow, Prefect, Make, Zapier)Experience with OpenAI, Anthropic, or similar LLM ecosystemsExperience building retrieval systems or internal knowledge basesBackground in e-commerce, wholesale, or operations-heavy environmentsWhat This Role OffersOwnership of the entire data and AI automation ecosystemA chance to build from scratch: pipelines, agents, tooling, and internal intelligence systemsDirect work with executive leadership and major influence on company operationsThe ability to dramatically reduce manual workload across teams through automationA high-impact role where your work is used daily across the organization