Job Details

Title: Procurement Data Strategy & Analytics Consultant

Pay: $85-$90 per hour

Type: Hybrid San Francisco California 94015

Duration: 6 months

Position Overview:

OpenAI's Procurement Center of Excellence (COE) is building an AI-enabled procurement analytics and reporting foundation so leaders and operators can make decisions with trusted data, and enable automation with clean, policy-aligned inputs. This role sits at the center of that effort: unifying data across our procurement stack, owning definitions/governance, and turning messy operational signals into durable self-serve insights.

We're looking for a Procurement Data Strategy & Analytics Senior Manager to architect and own the end-to-end procurement data foundation—from master data governance to production-grade pipelines and dashboards—spanning key Procurement, T&E, and Extended Workforce tooling.

You'll build and maintain trusted procurement dashboards from well curated datasets—turning spend, supplier, and cycle-time data into self-serve insights that improve decision-making, user experience, and compliance visibility (and that power automation and GPT-agent workflows).

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week.

Key Responsibilities:

• Partner with our Enterprise Systems & Platform Team to architect a unified procurement data mart spanning Zip, Oracle, Ironclad, VNDLY, Navan, Salesforce, and analytics tools—so Procurement can operate with real-time, trusted intelligence.
• Partner with our Enterprise Systems & Platform Team to build production-grade datasets and pipelines (e.g., in Databricks or equivalent), with consistent join logic, normalized tables, and data quality controls that hold up at scale.
• Own procurement master data and governance (suppliers, categories, items, entities, cost centers): design and enforce schema, validation logic, taxonomy alignment, and consistent definitions across systems.
• Design the procurement data layer that powers AI and automation — ensuring structured, validated datasets that enable GPT agents, workflow automation, anomaly detection, and intelligent routing across procurement operations.
• Deliver dashboards + self-serve reporting Source-to-Contract, Procure-to-Pay, T&E, and Extended Workforce.
• Enable AI agents and procurement automation by ensuring clean, validated datasets—so intelligent workflows operate reliably and don't stall due to incomplete or misaligned inputs.
• Harmonize KPIs and metric definitions across Sourcing, P2P, T&E, and Extended Workforce and act as the central owner of procurement metrics, KPI definitions, monthly reporting, and analytics governance.
• Monitor data health + close the loop operationally: resolve mismatches and exceptions, reduce supplier duplication/category misclassification, and eliminate recurring “manual triage” caused by bad data.
• Drive analytics adoption and be a champion for data maturity: replace ad hoc spreadsheets with governed pipelines and dashboards; publish enablement materials and measurement plans so XFN partners actively use Procurement intelligence.

Sample metrics include:

• supplier spend and performance insights
• intake SLAs / approval velocity / cycle time
• audit flags, exceptions, and compliance visibility
• escalations, rework, and workflow bottlenecks

Qualifications:

• 8+ years building data strategy, analytics, and/or data products for Procurement, Finance Ops, Supply Chain, or adjacent operational domains.
• Proven track record to partner with upstream technical teams to design a procurement data model end-to-end (supplier, spend, contract, intake/workflow, PO/invoice/payment, T&E, contingent workforce), including KPI definitions and canonical datasets.
• Hands-on experience building trusted datasets and dashboards that enable self-serve insights—turning spend, supplier, and cycle-time data into decision-ready reporting and compliance visibility
• Expert at creating compelling data visualization with dashboarding tools (e.g. Tableau, Zip, Navan, VNDLY, Oracle)
• Has experience with SQL and familiarity with analytics engineering concepts (data modeling, dimensional modeling, ELT/ETL patterns, testing/monitoring, documentation) so as to be a good XF partner.
• Enforce high standards upon partner data/engineering teams to build production-grade pipelines (e.g., Databricks or similar) with data quality checks, lineage, and governance.
• Expertise in procurement master data management: supplier/vendor master, taxonomy/category hygiene, item/service classification, entity/cost center alignment, and deduplication/normalization.
• Demonstrated success establishing data governance: metric definitions, source-of-truth alignment, access controls, change management, and audit-ready traceability.
• Strong track record translating ambiguous business needs into clear analytics requirements and together shipping data products iteratively with measurable impact (cycle time, rework reduction, SLA adherence, compliance).
• Excellent cross-functional collaboration skills—able to align Procurement, Finance, Legal, Security, and Enterprise Tech on definitions, workflows, and reporting.
• Ability to operate in a high-growth environment: high ownership, fast execution, comfort with ambiguity, and a bias toward automation and scalable solutions.