Divergent is a technology company that has architected, invented, built, and commercialized an end-to-end factory system called the Divergent Adaptive Production System (DAPS) that comprehensively uses machine learning to optimally engineer, additively manufacture, and flexibly assemble complex integrated vehicle structures and subsystems.

Requirements

, faster to market, and scalable on demand to high volume production. Divergent is a qualified Tier 1 supplier to global automotive OEMs, and Divergent is now expanding to support mission critical needs in the Aerospace and Defense sector. Join us to be a part of this transformative journey, where your impact will shape the future of technology and production.

Purpose Divergent is a technology company, based in Los Angeles, on a mission to build the 21st century industrial base with its proprietary Divergent Adaptive Production System (DAPS™). We automate the design, manufacture, and assembly of complex structures using non-design specific software, additive manufacturing, and robotic assembly. We actively work with governments, major automotive OEMS and aerospace primes globally, addressing the automotive, aerospace, aviation, transportation, and agricultural industries.

We are seeking a hands-on, technical candidate to be the driver of our production data systemization and simulation efforts. As a member of the team, this candidate will operate at the intersection of manufacturing operations, data, and strategy and will be responsible for scoping, conceptualizing, and implementing high impact tools that drive factory operations. You will act as a translator between functional groups and leadership, partnering with cross functional stakeholders (Factory Data Acquisition, Data, Software, and Operations) to turn messy systems data into actionable insight.

This is an applied, hands-on role that combines data architecture, analysis, and system design to make our operations measurable, predictable, and optimizable. The Role Partner with leadership to define, implement, and operationalize a measurement framework that translates raw data into structured parameters - revealing operational efficiency, quality, and financial insights. Standardize our inputs/outputs across models to create continuity between forecasting, scheduling, cost, and pricing.

Extend, tune, and maintain a discrete-event simulation that drives factory performance, forecasts demand, and simulates factory scaling scenarios. Prototype 0 à 1 parameterized data models and internal tools - including optimization tools, state machines, dashboards and simulation models that drive behavior across floor level operators, managers and executives. Collaborate with factory operations and engineering teams to identify tool gaps and scope and drive internal and external tool implementations.

Collaborate with factory data teams to identify data gaps and scope and drive projects to connect factory sensors, equipment, MES, ERP, and other operational systems. Drive projects through discovery, requirement definition, data backed proposal, functional prototyping, and formal implementation - including business case modeling and ROI justification for internal or external tool investments. Conduct a broad range of ad-hoc analysis spanning from process efficiency to complex scenario analyses that inform scheduling, staffing, and investment decisions.

Create presentations, visual workflows, diagrams, and prototypes to communicate complex problems clearly and align stakeholders in a common direction. Clean, validate, and prepare data for analysis and simulation. Document systems, pipelines, and assumptions clearly to enable scaling.

Qualifications

Ability to lawfully access information and technology that is subject to US export controls Bachelor’s or Master’s in Engineering, Data Science, Data Analytics, Ope

Operations Analyst