An Operations Analyst with a focus on manufacturing analytics is sought to transform production data into actionable operational insights and decision-making tools. This mid-level role involves applying statistical and machine learning methods to production data, developing models for granular time and cost prediction, and unifying factory data sources into a cohesive data model. The analyst will collaborate with the central Data team to operationalize this data and work with cross-functional teams to expose data where it doesn't yet exist. The position encompasses various Manufacturing Intelligence workstreams, including process improvement, simulation, equipment connectivity, and factory scaling, as priorities evolve.
Responsibilities
Develop and validate statistical and ML models correlating process time, staffing, and engineering data to enable granular time and cost prediction, with initial application in pricing and future extension to simulation and factory scaling
Unify equipment, MES, ERP/BOM, staffing, and engineering data into a cohesive data model to serve 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
Requirements
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 a 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
Millions of jobs, with real people getting hired every day
200,000+
New jobs added daily
7,000,000+
Verified job listings
1,000,000+
Tailored applications submitted
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
Nice to have:
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
Benefits
Holistic Compensation Package: Enjoy a world-class compensation package that includes an equity plan and discretionary results-based incentive bonus opportunities
Wellness and Time Off: Paid vacation, sick time, and company holidays, including a year-end shutdown. Paid parental leave
Comprehensive Health and Wellness: Comprehensive health and wellness benefits, offering both HMO and Premium PPO options. Company-sponsored life insurance and short and long-term disability coverage
Investment in Growth: Reimbursement opportunities for learning and development initiatives
Collaborative and High-Performing Environment: Join a collaborative, dynamic, and high-performing team within a fast-paced, mission-driven company
Important Details
Work Environment: Office (desk work, programming, and design tasks) and shop floor (machine operation, handling parts, exposure to high noise levels, machine electrical systems, and varying temperature conditions)
About the Company
Divergent is building the new industrial age, designing, manufacturing, and assembling advanced systems for some of the world’s most demanding industries. Its 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.
Divergent has created the world's first end-to-end software-hardware production system for industrial digital manufacturing – the Divergent Adaptive Production System (DAPS™) – allowing customers to design, additively manufacture, and automatically assemble complex structures for automotive, aerospace, and defense applications.
