Operations Analyst at Divergent

Job description

Divergent is building the new industrial age. Every day, our teams design, manufacture, and assemble advanced systems for some of the world’s most demanding industries. Our integrated engineering and manufacturing platform transforms complex designs into production-ready solutions, helping customers move faster, build smarter, and deliver critical systems when they matter most. Divergent is a qualified Tier 1 supplier to global automotive OEMs and supports leading U.S. aerospace and defense companies. Join us and help push the boundaries of what can be built. Purpose We are seeking a mid-level Operations Analyst with a manufacturing analytics focus to turn production data into operational insight and decision tools. This candidate will apply statistical and machine learning methods to production data and help develop models for granular time and cost prediction, unifying factory data sources into a cohesive data model. The analyst will partner with the central Data team to operationalize this data and, where data does not yet exist, partner with cross-functional teams to drive its exposure. The role spans Manufacturing Intelligence workstreams, including process improvement, simulation, equipment connectivity, and factory scaling, as priorities shift. The Role Develop and validate statistical and ML models correlating process time, staffing, and engineering data to enable granular time and cost prediction; initial application in pricing, extending to simulation and factory scaling. Unify equipment, MES, ERP/BOM, staffing, and engineering data into a cohesive data model that serves as a shared foundation for pricing, simulation, factory scaling, predictive models, and the team’s broader set of tools. Define source mappings, metric definitions, and data quality rules, including anomaly detection to flag inconsistencies in data inputs (e.g., work orders); partner with the central Data, AI, and Software teams to operationalize data and software tools. Identify operational inefficiencies and implement data-driven process improvements with operations and automation teams, validating data against shop floor conditions. Lead cross-functional projects from discovery and requirements through prototyping, business case and ROI justification, and implementation. Conduct ad hoc and scenario analyses supporting pricing, capacity, staffing, and investment decisions. Communicate and document data models, methodology, and assumptions for technical and non-technical stakeholders. Basic Qualifications Ability to lawfully access information and technology that is subject to US export controls Bachelor’s or Master’s in Data Science, Statistics, CS, Operations Research, or related field (or equivalent experience) Demonstrated experience in operations analytics, analytics engineering, data science, or data-intensive manufacturing roles Hands-on experience with production data and shop floor execution in a manufacturing environment, including work orders, BOMs, routings, and production scheduling Python: pandas, NumPy, scikit-learn, statsmodels, matplotlib/Plotly; data extraction, API integration, task automation SQL: complex joins, window functions, CTEs; relational data modeling; cleaning and validation of high-volume operational and time-series data Applied statistics and supervised ML: hypothesis testing, regression, classification, tree-based ensembles; feature engineering, cross-validation, model evaluation; anomaly detection for input data validation Manufacturing operational metrics (cycle time, yield, throughput, utilization, OEE, WIP) Git; documented, reproducible code Integration of AI tools into daily workflow Independent project ownership and management: scoping, requirements gathering, timelines, dependencies, and stakeholder alignment without prescriptive direction Translation of ambiguous business problems into structured problem statements and analytical approaches Communication of technical concepts and model outputs as decision-ready recommendations for non-technical stakeholders Iterative, prototype-first delivery and MVP prioritization Direct engagement with shop floor personnel for requirements, data validation, and implementation Execution across concurrent workstreams in a fast-paced, dynamic environment Preferred Qualifications Microsoft Fabric or equivalent lakehouse platforms (Databricks, Snowflake): navigation and data extraction MES/ERP data structures (work orders, routings, BOMs, genealogy, NCRs) Equipment data flows, IIoT protocols, and time-series data (OPC‑UA, MTConnect, MQTT, historians) Discrete-event simulation (SimPy, AnyLogic) and optimization methods (LP/MIP, OR-Tools) Additive manufacturing and metal process chains (LPBF, heat treatment, CNC machining, CMM/CT inspection) Engineering drawings, GD&T, and CAD Cost accounting, pricing, and financial modeling (unit economics, margin, ROI) Lean and continuous improvement methods (Six Sigma, DMAIC, process mapping) and shop floor change management Project management tooling (Atlassian Suite, Smartsheet) and Agile methods Technical knowledge transfer and mentorship Start-up, consulting, or similar high-growth environment 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. Pay Range $100,170 — $137,730 USD What We Offer: Holistic Compensation Package: Enjoy a world-class compensation package that includes a competitive salary, equity plan, and discretionary results-based incentive bonus opportunities, ensuring you're truly valued for your contributions. Wellness and Time Off: Embrace a healthy lifestyle with paid vacation, sick time, and company holidays, including a year-end shutdown to recharge. We support growing families with paid parental leave, recognizing the importance of bonding time. Comprehensive Health and Wellness: Prioritize your well-being with our comprehensive health and wellness benefits, offering both HMO and Premium PPO options. Additionally, benefit from company-sponsored life insurance and short and long-term disability coverage for peace of mind. Investment in Growth: We're committed to your professional development. Take advantage of reimbursement opportunities for learning and development initiatives, empowering you to continuously expand your skill set and reach peak performance. Collaborative and High-Performing Environment: Join our collaborative, dynamic, and high-performing team within a fast-paced, mission-driven company. Together, we're disrupting the traditional manufacturing industry, fostering innovation, and integrating people and technology to reduce our footprint. Equal Employment Opportunity Divergent is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected characteristic. Divergent provides affirmative action in employment for qualified Individuals with Disabilities and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act. EEO Poster In order to adjust to changes in our business, it may become necessary to add, remove or modify certain duties and responsibilities, or to reassign you to another job position. From time to time you may be asked to work on special projects or to assist with other work. Your cooperation and assistance in performing such additional work is expected. E-Verify: Right to Work Our company participates in E-Verify . E-Verify is a program that electronically confirms a candidate’s eligibility to work in the United States after completing the Employment Eligibility Verification (Form I-9). The information provided on the Form I-9 is compared to the records contained in the Social Security Administration and Department of Homeland Security (DHS) databases. This helps employers verify the identity and employment eligibility of newly hired employees. Eligibility to Work Poster (English) | Eligibility to Work Poster (Spanish) Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO) Pursuant to the Los Angeles Fair Chance Initiative for Hiring Ordinance (FCIHO), we will consider for employment qualified applicants with arrest and conviction records. No agencies, no solicitations, and no calls please.

Requirements

Must-haves

Join us and help push the boundaries of what can be built. Purpose
Identify operational inefficiencies and implement data-driven process improvements with operations and automation teams, validating data against shop floor conditions.
Lead cross-functional projects from discovery and requirements through prototyping, business case and ROI justification, and implementation.
Conduct ad hoc and scenario analyses supporting pricing, capacity, staffing, and investment decisions.
Communicate and document data models, methodology, and assumptions for technical and non-technical stakeholders.
Ability to lawfully access information and technology that is subject to US export controls
Bachelor’s or Master’s in Data Science, Statistics, CS, Operations Research, or related field (or equivalent experience)
Demonstrated experience in operations analytics, analytics engineering, data science, or data-intensive manufacturing roles
Hands-on experience with production data and shop floor execution in a manufacturing environment, including work orders, BOMs, routings, and production scheduling
Python: pandas, NumPy, scikit-learn, statsmodels, matplotlib/Plotly; data extraction, API integration, task automation
SQL: complex joins, window functions, CTEs; relational data modeling; cleaning and validation of high-volume operational and time-series data
Applied statistics and supervised ML: hypothesis testing, regression, classification, tree-based ensembles; feature engineering, cross-validation, model evaluation; anomaly detection for input data validation

Nice-to-haves

Microsoft Fabric or equivalent lakehouse platforms (Databricks, Snowflake): navigation and data extraction
MES/ERP data structures (work orders, routings, BOMs, genealogy, NCRs)
Equipment data flows, IIoT protocols, and time-series data (OPC‑UA, MTConnect, MQTT, historians)
Discrete-event simulation (SimPy, AnyLogic) and optimization methods (LP/MIP, OR-Tools)
Additive manufacturing and metal process chains (LPBF, heat treatment, CNC machining, CMM/CT inspection)
Engineering drawings, GD&T, and CAD
Cost accounting, pricing, and financial modeling (unit economics, margin, ROI)
Lean and continuous improvement methods (Six Sigma, DMAIC, process mapping) and shop floor change management
Project management tooling (Atlassian Suite, Smartsheet) and Agile methods
Technical knowledge transfer and mentorship
Start-up, consulting, or similar high-growth environment
Work Environment

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlaipythonapisqlagile

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Parental Leave

Wellness

Professional Development