Lead Data Analyst, Manufacturing Operations

About Rivian

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.

As a company, we constantly challenge what's possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

We're seeking a visionary Lead Data Analyst, Manufacturing Operations within our Plant Controllership program to lead the design and delivery of Rivian's next-generation manufacturing analytics ecosystem. This senior individual contributor will drive the strategy and execution for real-time cost convergence, shop-floor telemetry integration, and "financial digital twin" architecture—leveraging our vast operational data to build first-of-their-kind predictive FP&A products. The ideal candidate brings deep technical controllership expertise, strong industrial data science acumen, and the leadership to scale data-driven decision-making in a rapidly evolving EV production environment.

Why This Role Matters:

• Redefine Manufacturing Unit Economics: Build Rivian's strategy for integrating real-time shop floor signals (MES, SCADA), labor dynamics, and material flow into live financial models, moving beyond static standard costing.
• Lead Predictive Cost Innovation: Be among the first in the industry to model and launch "preventative financial maintenance" algorithms—detecting yield loss and margin erosion anomalies before the month-end close.
• Controllership Meets Data Science: Apply predictive analytics, automated variance causation modeling, and BOM-level granularity to drive safer, smarter, and more precise capital allocation.
• Build a Platform: Lead a cross-functional initiative at the intersection of data engineering, plant operations, and finance to democratize "cost-per-second" insights.
• Shape Operational Finance Standards: Work with Plant Directors and the C-Suite to define next-gen KPIs and automated governance frameworks that link physical production to P&L outcomes.

• Lead the manufacturing analytics strategy for Rivian's Plant Controllership and Operations Finance functions.
• Design and deploy scalable data pipelines (ETL/ELT) and ML algorithms for automated root cause analysis of financial variances (isolating scrap, usage efficiency, and labor rate impact).
• Measure and quantify the financial impact of operational constraints—such as bottleneck uptime, micro-stoppages, and OEE fluctuations—across vehicle programs.
• Build and deploy new cost-monitoring products aligned with Rivian's in-plant technology ecosystem (SAP S/4
  
  HANA, MES, Kronos), including granular Hours Per Vehicle (HPV) and First Pass Yield (FPY) attribution models.
• Conduct deep profitability and contribution margin analysis for Rivian's production lines using high-frequency operational data.
• Act as a technical leader across the Finance, Data, and Operations organizations, bridging the gap between "physical" shop floor events and "financial" ledger outcomes.
• Optimize the month-end close and forecasting cycles through the development of resilient, auditable dashboards in Databricks, Hex, and Tableau
  .
• Mentor and develop the technical capabilities of the broader Plant Finance team, establishing coding standards and best practices for financial data engineering.

Required Qualifications:

• 7+ years of progressive experience in data analytics, business intelligence, or financial systems, specifically within Manufacturing, Supply Chain, or Industrial Finance settings.
• Deep experience with manufacturing cost accounting concepts:
  Standard Costing, Bill of Materials (BOM) explosion, WIP valuation, and absorption logic.
• Proven leadership in architecting analytics platforms that solve complex operational problems.
• Strong command of SQL (Window functions, CTEs, optimization) and Python (Pandas, Num Py) for advanced data manipulation and modeling.
• Demonstrated success working with ERP systems (SAP S/4
  
  HANA preferred)…