Lead Data Analyst, Manufacturing Operations

Rivian • Normal, IL

4h

About The Position

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.

Requirements

• 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, NumPy) for advanced data manipulation and modeling.
• Demonstrated success working with ERP systems (SAP S/4HANA preferred) and unifying them with operational data sources (MES, Timekeeping/Kronos).
• Strong executive communication and stakeholder management skills; ability to translate complex technical findings into strategic business guidance.

Nice To Haves

• Prior experience in automotive or high-volume EV manufacturing environments.
• Expertise in modern data stack tools: Databricks, Spark, dbt, or similar cloud-based engineering platforms.
• Advanced degree (Master’s) in Engineering, Finance, Computer Science, or a related quantitative field.
• Passion for mobility innovation, sustainable manufacturing, and building "zero-defect" financial data cultures.

Responsibilities

• 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/4HANA, 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level