Data & AI Product Analyst

About Axya

Axya is building AI-powered technology that's transforming how the manufacturing industry sources and procures parts. Our platform connects manufacturers with suppliers and automates the entire source-to-pay process — from sourcing and quoting to procurement — making it faster, simpler, and more cost-effective for companies sourcing custom parts. By digitizing traditionally manual workflows, Axya enables manufacturers to operate with greater efficiency and competitiveness.

We are proud to cultivate an inclusive and collaborative work environment that fosters innovation, growth, and professional development. As a member of our team, you'll collaborate with passionate, forward-thinking professionals and contribute directly to transforming procurement in the manufacturing sector.

Role Overview

We're hiring a Data & AI Product Analyst to build the first version of the data products our Customer Success team keeps discovering the need for: analytics, reporting, and AI-driven insight workflows rooted in real supply chain and procurement problems we see in customer data.

This is an individual-contributor, builder role — not a product management role, and not a people-management role. You work directly with the VP of Customer Success to pick opportunities grounded in tangible client data (an account with fragmented spend across many ERPs, a customer asking for AI-assisted RFQ recommendations, a prospective account that needs a data-backed business case to sign). You go from raw data to a working prototype fast, using common prototyping tools — Available frontier models (with MCP or API), n8n, Metabase/SQL, APIs, and whatever SaaS tooling our Product infrastructure makes available — and you validate whether it creates real, provable value for the customer.

You bring the product-management instinct to scope a lean MVP and know what ‘good enough to prove value’ looks like, paired with individual-contributor execution — you build it yourself. When a prototype proves out, you package the spec, the learnings, and the business case, and hand it to the Product team to take from one to scale. You are the tip of the spear on unproven, high-upside ideas; you are not building the roadmap, and you are not the one who scales what works. Some bets will fail fast and get killed — that's expected and fine.

Key Responsibilities

1. Customer Data Product Prototyping (0→1)

• Turn a live customer opportunity into a working prototype: cross-ERP spend visibility for accounts with many business units, AI-assisted RFQ price recommendations embedded in the buyer's workflow, savings analyses that quantify what a prospective account is leaving on the table, Improved on-time-delivery opportunities.
• Build with the fastest tool for the job — LLM/MCP for analysis and drafting, n8n for workflow automation, Metabase/SQL for reporting, direct API/data work when no-code runs out of room
• Iterate on real customer feedback, not assumptions — ship something usable within days/weeks, not a polished product

2. Domain-Led Discovery

• Partner with the VP of CS to identify which accounts and opportunities justify a data-product bet, based on account data and expansion/retention signal
• Run discovery directly with customers' procurement, sourcing, or supply chain stakeholders — you need to understand their world well enough to know what's worth building
• Bring genuine curiosity about supply chain data: pricing variance, supplier concentration, sourcing patterns, RFQ behavior — you enjoy digging into this, not just processing it

3. Business Case & Value Proof

• Quantify impact in terms an executive will act on — dollars saved, cycle time recovered, risk reduced
• Build the reporting and demo artifacts that make the business case credible: before/after views, savings dashboards, live walkthroughs
• Know when something isn't working and say so — a fast, honest ‘no’ is as valuable as a win

4. Hand-off for Scale

• Once a prototype is validated, document the data model, the workflow, and the proof points needed for Product/Engineering to rebuild it for scale
• Stay involved as the domain expert through the transition, without owning the productized roadmap

What We’re Looking For

• Hands-on experience turning messy, real-world data into a working analysis, report, or prototype — start to finish, on your own
• Comfortable with SQL and a BI tool (Metabase or similar), plus API/JSON work
• Working knowledge of modern AI/LLM tooling (Claude/GPT/…) and no-code/low-code automation (n8n or equivalent) — or the demonstrated ability to pick it up fast
• Strong business communication — you can turn a dataset into a one-page recommendation an executive will act on
• Product-management instincts: you can scope a lean MVP and resist over-building
• 3–5+ years of relevant experience — supply chain/procurement analytics, ops engineering, data analytics, consulting, or a founding/early-builder role all count

Preferred (Axya-Specific)

• Direct experience in supply chain, procurement, or manufacturing operations, or with ERP data (SAP, Epicor, Genius, Kinetic, or similar)
• Prior product management or founding-engineer experience

• Experience presenting data-backed recommendations to enterprise executives
• Light Python/JavaScript — enough to write a script when no-code runs out of room
• French is a plus

Why Join Axya

• 🏖 Unlimited vacation policy: because we believe in balance.
• 🏥 Comprehensive health insurance: your well-being matters.
• 🕒 Flexible work schedule: results matter more than hours.
• 🏡 100% remote: get the job done wherever you prefer.

• 🚀 Be part of a high-impact, collaborative team making real change in a traditional industry.