Data Scientist - Los Angeles, CA

Lab37•Los Angeles, CA

2h•Onsite

About The Position

Lab37 Robotics is a technology company focused on the development and deployment of robots designed specifically for direct-to-customer food production. Our mission is to revolutionize the food industry by creating innovative robotic solutions that enhance efficiency, quality, and customer satisfaction. We are passionate about pushing the boundaries of technology to deliver cutting-edge products that meet the evolving needs of our industry. The Data Scientist will own the forecasting, analysis, and optimization models that turn Lab37’s customer and operational data into reliable decision systems. This role involves translating ambiguous problems into structured models that inform product, operations, and business decisions, and driving models from concept through deployment while balancing accuracy, interpretability, latency, and real-world impact.

Requirements

Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Operations Research, or a related quantitative field
7-10 years of relevant work experience in data science, machine learning, statistics, operations research, or similar domains.
Track record building and deploying models that drive measurable business impact.
Strong analytical and statistical rigor; able to diagnose performance, identify root causes, and quantify tradeoffs.
Strong programming skills (e.g., Python, SQL) with the ability to build production-ready data pipelines and models.
Systems-thinking mindset; able to model complex, constraint-driven environments end-to-end.

Nice To Haves

Experience with operations research or constraint-based optimization (e.g., LP/MIP, scheduling, resource allocation).
Experience building simulation models for complex, real-world systems (e.g., discrete-event or digital twins).
Experience working with real-time operational or telemetry data in production environments.
Experience in food service, on-demand delivery, or just-in-time manufacturing / production systems.

Responsibilities

Perform in-depth data analysis to identify trends, patterns, and insights.
Develop statistical models and machine learning algorithms to solve business problems.
Create and maintain dashboards and reports to visualize key metrics and communicate findings.
Help define Lab37's overarching data infrastructure, standards, and governance policies.
Design, build, and maintain robust and scalable data pipelines for various data sources.
Ensure data quality, integrity, performance, and reliability across all pipelines.
Model and optimize end-to-end system decision variables across the operational ecosystem.
Define objective functions that formalize tradeoffs (cost, quality, timing, customer experience).
Build optimization systems that continuously re-plan as inputs and conditions change.
Develop simulation tools for “what-if” analysis to guide product and operational decisions.
Partner with operations, product, and engineering teams to translate data into crisp requirements.
Communicate complex concepts clearly to technical and non-technical stakeholders.
Support business operations with data-driven insights and analysis.