---
title: 'Data Scientist - Supply Chain at Auger'
canonical: 'https://feeny.ai/job/data-scientist-supply-chain-auger-bellevue-2gzs2y0xfes2'
type: 'job'
last_seen: '2026-09-09'
---

# Data Scientist - Supply Chain at Auger

- **Company:** Auger
- **Location:** Bellevue, WA
- **Compensation:** $145k–$200k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-06-15
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.gem.com/auger/am9icG9zdDrHO0jn_1h21JwAuHW6RXmu

## Job description

## About the Team & Role

Auger is hiring a Data Scientist to help turn raw customer data into the structured understanding within our ontology that powers autonomous operations and execution. Russell Allgor’s supply chain science team builds advanced AI and optimization systems for some of the most complex supply chain problems in the world, and bringing that science into production requires a tight connection between the models and the data that feeds them. This role sits at that connection point.

You will work shoulder-to-shoulder with seasoned supply chain experts, learning the domain on the job while bringing the analytical horsepower to model it. Your core work will be to understand how a customer’s business actually operates, interpret the data their systems produce, and build the inference, regression, simulation, and optimization logic that closes the loop between business processes and the world model that represents them. You will deeply understand what the models need, why they need it, and how supply chain data behaves in practice, then translate that understanding into clear, actionable requirements for the engineers building the underlying infrastructure.

You will be a critical link between Auger’s applied science and data engineering teams. When data quality issues arise, you will help diagnose whether the issue is the source data, a pipeline problem, a modeling assumption, or a mismatch between the data and the real-world business process it represents. When a model moves toward production, you will own the quality validation to make sure it works in the real world.

This is a role built for potential. We care far more about how you think — how you question things that don’t make sense, break a hard problem into testable pieces, and use data to prove or disprove a hypothesis — than about the length of your résumé. If you are smart, curious, driven, and coachable, and you like to build things that work, you will thrive here.

This role is based in Bellevue, WA or Dallas, TX

## What You’ll Do

- Understand how customer businesses actually operate: how work flows, where decisions are made, and what good looks like operationally.
- Interpret customer data and assign context — figure out what the data means, how entities relate, and where the gaps and inconsistencies are.
- Form and test hypotheses using data to prove or disprove ideas about the system and the relationships between entities within it.
- Build inference techniques and regression models that extract signal and quantify relationships.
- Translate business logic and objectives into mathematical constraints and quantifiable calculations.
- Identify missing concepts needed to close process and data loops — spot what isn't there yet but needs to be.
- Serve as the critical link between applied science and data engineering: translate scientific requirements into engineering specifications and vice versa.

## What You Bring

- Master's degree in Data Science, Statistics, Applied Mathematics, or a related quantitative field; undergraduate degree in Engineering, Mathematics, Economics, or Computer Science.
- Strong proficiency in Python and SQL; comfortable working with large, messy, real-world datasets.
- Experience with machine learning and optimization models, with strong statistical intuition — you notice when results look wrong and can articulate why.
- Enough familiarity with data pipelines and infrastructure to have productive technical conversations with data engineers.
- Sharp analytical instincts paired with strong common sense: you can tell when something doesn't add up, and you use data to prove or disprove it.
- A builder's mindset — you break problems into testable components, take things apart, and improve them.
- Comfort with ambiguity and a bias toward asking the right question before assuming the right answer.
- Supply chain and logistics experience is ideal. Hands-on experience with any complex, interrelated physical system is highly beneficial. Candidates who demonstrate the smarts, drive, and curiosity described above are encouraged to apply — we hire for potential.

## About Auger

## Company Overview
- **One-liner**: Auger is building the world’s first autonomous operating system for supply chain operations, collapsing the gap between signal and execution with AI-powered automation.
- **Entity Type**: Private (Series A)
- **Headquarters**: Bellevue, Washington, USA
- **Founded**: 2024
- **Founders**: Dave Clark (Founder & CEO), Leigh Anne Clark (Co-Founder and President, Fashion and Beauty)

## Core Business
- **Primary industry/industries**: Supply Chain Technology, Enterprise AI, Logistics Software
- **Target customers**: B2B, Enterprise (large-scale supply chain operators, retailers, manufacturers, logistics providers)
- **Mission or purpose statement**: "To eliminate the Coordination Tax that traps enterprises in manual silos and fragmented systems. To make superhuman operations available to every enterprise ready to lead."

## Products & Services
- **The Autonomous Operating System**: A unified AI-powered platform that integrates with existing enterprise systems to provide real-time intelligence, cross-system synchronization, and autonomous execution of routine supply chain tasks (demand shifts, lead time management, capacity planning, scheduling). The system turns messy data into executable truth, allowing operators to move from firefighting to strategic work.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric – Total Funding**: $400M across three rounds (Seed, Series A, Series A extension)
- **Notable Investors/Partners**: Oak HC/FT (lead investor in initial $100M Series A)
- **Growth Signals**:
  - Headcount grew **223.9% YoY** (from ~26 to 129 employees)
  - LinkedIn follower count grew **74.5% YoY** (currently 12,855)
  - Active job postings: 17 (up 88.9% YoY)
  - Major talent pipeline from Amazon (26 hires), Microsoft (9), AWS (7), Meta (4)

## Competitive Advantages
- **Founder pedigree**: Led by Dave Clark, former CEO of Amazon’s worldwide consumer business — deep operational credibility at global scale.
- **"Living Ontology" approach**: Not layering AI on top of broken legacy systems, but building a unified data fabric across the entire enterprise.
- **Consumer-grade UX**: Makes complex supply chain tasks accessible through simple, intuitive interfaces (e.g., natural language queries for inventory insights).
- **Team composition**: 53% of employees in technical roles; includes a Chief AI and Agentic Scientist, Chief Supply Chain Scientist, and Chief AI Economist — rare depth of domain AI expertise.

## Strategic Focus
- **Autonomous execution**: Replacing the "speed of consensus" (manual coordination, meetings, spreadsheets) with real-time, automated reflexes.
- **Sustainability**: Positioning autonomous execution as the architecture for sustainable scaling — reducing excess inventory, expedited shipments, and waste.
- **Expanding beyond supply chain**: The company states it will expand "wherever coordination breaks down," suggesting a platform play across adjacent operational domains.

## Why Work Here
- **Culture highlights**: Described as a "pioneering venture" with a human-centered approach to solving broken supply chains. The team is composed of operators who "have lived the consequences" — late nights, impossible trade-offs — and are building to eliminate that pain for others.
- **Remote/hybrid/office policy**: In-office roles (e.g., Strategic BDR listed as "In-Office"). HQ in Bellevue, WA, with additional offices in Clyde Hill, WA and Bellevue, WA.
- **Notable perks or engineering culture**: Heavy investment in deep technical talent (AI, data science, supply chain science). Emphasis on moving from "firefighting to reinvention." Backed by top-tier VC with substantial runway ($400M total funding). Strong pipeline of ex-Amazon, Microsoft, and Meta engineers.

## Sources
1. [auger.com](https://auger.com/about/)
2. [linkedin.com](https://linkedin.com/company/augerinc)
3. [builtin.com](https://builtin.com/company/auger)
4. [cbinsights.com](https://www.cbinsights.com/company/auger)
5. [theorg.com](https://theorg.com/org/auger-1)

## Other roles at Auger

- [Customer Engineering Lead](https://feeny.ai/job/customer-engineering-lead-auger-bellevue-6zzen1qnj7za) — Bellevue, WA
- [Software Development Engineer](https://feeny.ai/job/software-development-engineer-auger-bellevue-v5g9bd4tykz8) — Bellevue, WA
- [Deployment Strategist](https://feeny.ai/job/deployment-strategist-auger-dallas-c7j3rqsgv615) — Dallas, TX
- [Principal Software Development Engineer](https://feeny.ai/job/principal-software-development-engineer-auger-bellevue-rst59fsvcgwm) — Bellevue, WA
- [Principal Product Manager - Platform Experience](https://feeny.ai/job/principal-product-manager-platform-experience-auger-bellevue-xvsrrkh9azm3) — Bellevue, WA
- [Applied Scientist - Supply Chain](https://feeny.ai/job/applied-scientist-supply-chain-auger-bellevue-gw6nyzm5ktcm) — Bellevue, WA
- [UX Engineer](https://feeny.ai/job/ux-engineer-auger-bellevue-k41b19gfq7ty) — Bellevue, WA
- [Software Development Engineer - Front-End](https://feeny.ai/job/software-development-engineer-front-end-auger-bellevue-8gc0qdn8jnn8) — Bellevue, WA
- [IT Operations Engineer](https://feeny.ai/job/it-operations-engineer-auger-dallas-8ffh6xd5ezmg) — Dallas, TX
- [Software Development Engineer - AI Enablement](https://feeny.ai/job/software-development-engineer-ai-enablement-auger-bellevue-880qjdq6kfny) — Bellevue, WA