Operations Analyst, Divergent Technologies

• 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, Operations Research, or related field (or equivalent experience)
• Demonstrated experience in data analytics, process improvement, or similar roles
• Strong proficiency in Python (pandas, NumPy, data pipelines, APIs, light scripting)
• Strong proficiency in SQL and relational data modeling
• Demonstrated ability to perform descriptive and diagnostic analysis, basic statistics, and visualization
• Demonstrated knowledge of manufacturing terminology and operational data modeling (cycle time, yield, throughput)
• Demonstrated competency with data visualization tools like Power BI (or related)
• Demonstrated competency with UI/workflow visualization tools (Figma, Illustrator, Visio)
• Strong experience with presentation/organizational tools (Microsoft Suite, Atlassian Suite, Project Management Software, Smartsheet)
• Experience gathering project requirements from stakeholders and taking a project from initial concept to finished product
• Strong presentation and oral skills with the ability to translate technical concepts to non-technical audiences for stakeholders internal and external to the organization
• Ability to translate messy and emergent business challenges into structured problem statements
• Focus on detail, iterative design, human centered design, and systems thinking
• Comfortable in a fast paced, dynamic environment
• Ability to lean on and implement AI tools into daily workflow
• Work Environment:
• Office: Desk work, programming, and design tasks
• Shop floor: Machine operation, handling parts, exposure to high noise levels, machine electrical systems, and varying temperature conditions

Desirable

• We are seeking a hands-on, technical candidate to serve as the backbone of our data 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 engineering, analysis, and system design to make our operations measurable, predictable, and optimizable
• Extend, tune, and maintain a discrete-event simulation that drives factory performance, forecasts demand, and simulates factory scaling scenarios
• Partner with leadership to define, implement, and operationalize a measurement framework that translates raw data into structured KPIs, revealing operational efficiency, quality, and financial insights
• Conceptualize internal tools including optimization tools, state machines, and dashboards that translate operational functions into parameterized data models to forecast, optimize, and 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
• Support and drive projects from discovery to full implementation, including requirement definition, data backed proposals, functional prototyping, and ultimately formal implementation via internal/external software teams
• Contribute to 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