Finance Analytics & AI Engineer

About the role

ABOUT SLATE At Slate , we're building safe, reliable vehicles that people can afford, personalize and love-and doing it here in the USA as part of our commitment to reindustrialization. The spirit of DIY and customization runs throughout every element of a Slate , because people should have control over how their trucks look, feel, and represent them. WHO WE ARE LOOKING FOR The Finance Analytics & AI Engineer is a senior individual contributor role based on the Commercial FP&A team, with scope to support the broader Finance organization. This role is the foundational technical hire responsible for architecting and building the reporting analytics and AI-driven automation that powers commercial decision making. A defining feature of this role is helping carry Finance reporting and analytics through Slate 's planned ERP migration from NetSuite to future-slate ERP platform (targeted for early 2027), ensuring data models, pipelines, and reporting remain stable and accurate across the transition. In the near term, NetSuite remains the system of record while future-slate ERP solution is implemented, so you should be comfortable building on NetSuite today and designing for portability to future-slate ERP solution. WHAT YOU GET TO DO Own the Finance Data & Intelligence Layer Architect and scale Slate 's Finance reporting and analytics ecosystem across all Finance functions - including Commercial and Corporate FP&A, Accounting/Controllership, Treasury, and Procurement - as well as partner organizations such as Product Development Design and maintain robust data models that integrate the ERP environment (NetSuite today, migrating to future-slate ERP platform by early 2027), EPM (Adaptive Planning), and operational systems Build scalable data pipelines and layers to enable self-service analytics through AI agents Lead Finance AI & Automation Strategy Define and execute Slate 's Finance AI roadmap, including: AI-powered variance analysis (PVM, BvA/FvA) Automated forecast updates and anomaly detection Inventory optimization Natural language query tools for business users Build and deploy AI agents that: Connect to finance and operational datasets Enable leaders to query performance (e.g., SKU-level GM trends, pricing impacts) Automate recurring Finance workflows Build Best-in-Class Dashboards & Reporting Develop executive-ready dashboards and reporting across: Gross margin by product, channel and unit economics Opex & Capex forecasting & actuals reporting Sales, inventory, and take rate analyses Plant KPI reporting (manufacturing cost, throughput, and operational performance) Business performance dashboard consolidating company-wide financial and operational KPIs for leadership Sales KPI tracking (bookings, deliveries, and channel performance) Partner Finance and Commercial stakeholders to standardize KPIs and reporting definitions Deliver real-time insights for leadership (including Board-level materials) Drive Advanced Analytics & Decision Support Develop models for: Pricing optimization and margin expansion Demand forecasting and inventory planning Scenario modeling and long-range planning Enable a Self-Service Data Culture Build tools that allow non-finance stakeholders to access and interpret financial data Implement data governance and output validation into AI models Train business partners on dashboards, tools, and AI capabilities Reduce manual reporting and elevate the organization toward real-time, insight-driven decision making WHAT YOU BRING We are seeking a highly technical, product-minded senior individual contributor who can bridge finance, data engineering, and AI. This person will be foundational in building Slate 's next-generation Finance function. 8+ years in FP&A, Business Intelligence, Data Analytics, or related fields - or equivalent demonstrated capability across FP&A, data engineering, and AI Strong finance acumen (P&L, gross margin, unit economics, forecasting) Advanced expertise in BI tools (Tableau, Power BI, Looker, etc.) Experience working with ERP/EPM systems (NetSuite and Adaptive Planning preferred) Strong SQL and data modeling capabilities Experience building data pipelines and working with data warehouses/lakes Familiarity with Python or similar for analytics and automation Experience integrating multiple data sources into a unified reporting layer AI & Automation Experience (Required) Demonstrated hands-on experience building and deploying AI/ML models, agents, and analytics workflows in production (not experimental or coursework only) Working proficiency with LLMs and agent-based architectures Experience using AI tools to automate reporting, forecasting, or analysis Strong interest in building AI-driven finance capabilities from the ground up Mindset Builder mentality: thrives in ambiguous, fast-moving environments Highly analytical with strong attention to detail Strong communicator who can translate data into business insights Ope

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