Full-Stack Data Scientist / ML Engineer

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

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 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