Auger

Applied Scientists - AI Economics

Reposted 8 Days Ago

Be an Early Applicant

Bellevue, WA, USA

In-Office

180K-250K Annually

Mid level

Software

The Role

The Applied Scientist will design, deploy, and scale ML systems for supply chain risk forecasting, collaborating with economists and data engineers to optimize sourcing decisions and ensure models run effectively in production.

Summary Generated by Built In

Build at Auger

Auger is the autonomous operating system for supply chains. It connects enterprise supply chain systems—ERP, WMS, TMS—into a single data layer, then uses AI to detect problems, evaluate trade-offs, and execute decisions automatically. The platform eliminates the coordination tax: the time and capital lost when disconnected systems force humans to become the integration layer between planning and execution. Actions that previously required days of meetings and manual coordination happen in seconds, within constraints the customer defines.

Founded by Dave Clark and backed by $100M from Oak HC/FT. Headquartered in Bellevue, Washington.

About the Role

The AI Economics Team at Auger is building an AI and agentic-powered market intelligence system that enables our customers to forecast supply chain risk, optimize sourcing decisions, and respond to global disruptions in real time. We are looking for an Applied Scientist to design, deploy, and scale the systems at the core of this platform.

You will own the end-to-end ML lifecycle for production systems including demand and cost forecasting models, supplier reliability prediction, NLP pipelines for news and document intelligence, and real-time cost calculation engines. Your work will directly inform sourcing recommendations that move billions of dollars in procurement spend.

This role sits at the intersection of applied ML and economics research and production engineering. You will collaborate closely with economists on causal inference methodology, with data engineers on feature pipelines, and with product teams to translate model outputs into actionable customer-facing tools. You should be comfortable shipping models that run at scale, monitoring their performance in production, and iterating based on real-world feedback.

Our current technical stack includes time-series forecasting (demand signals, commodity prices, delivery timing), causal ML for supplier effect estimation, NLP for document parsing and news sentiment (certificates of origin, compliance documents, global news feeds), and real-time scoring APIs serving predictions to interactive dashboards.

What You Bring

4+ years experience building and deploying ML models in production environments
Strong proficiency in Python and ML frameworks (scikit-learn, XGBoost/LightGBM, PyTorch)
Experience with time-series forecasting methods (ARIMA, Prophet, gradient boosting, neural forecasters)
Familiarity with NLP pipelines: text classification, named entity recognition, document parsing, or sentiment analysis
Production ML infrastructure: model serving, feature stores, monitoring, retraining workflows, and deployment into existing CI/CD systems(including unit tests and integration tests)
SQL proficiency and experience with data pipeline tools (Airflow, dbt, or similar)
Ability to communicate model behavior and limitations to non-technical stakeholders

Compensation & Benefits

As part of our commitment to People Powered Greatness, we invest in our team members with competitive compensation and a comprehensive benefits to support your health, financial future, and daily life. The package includes medical, dental, and vision coverage, a 401(k) with company match, and commuter benefits. Total compensation may include a combination of a competitive base salary and equity. Your initial placement within our salary range will be based on your experience, qualifications.

The base pay range for this role is $180,000 – $250,000 per year.

Auger considers all qualified applicants for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Additionally, our privacy policy is available at https://auger.com/privacy-notice/.

Skills Required

4+ years experience building and deploying ML models in production environments
Strong proficiency in Python and ML frameworks
Experience with time-series forecasting methods
Familiarity with NLP pipelines
Production ML infrastructure experience
SQL proficiency and experience with data pipeline tools
Ability to communicate model behavior and limitations

View all jobs at Auger

View Auger Profile

Report Job

Am I A Good Fit?

beta

Get Personalized Job Insights.

Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company

HQ: Bellevue, WA

35 Employees

What We Do

About Auger Auger is a pioneering venture to build the world's first true end-to-end supply chain operating system. Founded and led by Dave Clark, former CEO of the Amazon Consumer Business and backed by an initial $100M from Oak HC/FT, Auger is building a future where global supply chains operate with the simplicity of today’s most intuitive consumer technologies. Revolutionizing global supply chains with an AI-powered OS unifying data for seamless, real-time insights, and powerful automation. Our Solution Auger is creating a new solution for companies seeking better options. Auger’s core strength lies in its deep AI-powered automation, paired with a consumer-grade user experience. This combination allows operators to handle complex tasks through simple, familiar tools. Need real-time inventory insights for next week’s shipment? Just ask. Actionable data appears instantly, enabling swift decisions—no complex queries or training required. Why We’re Different Traditional supply chain management is fragmented, relying on incompatible systems and inefficient workarounds. Many companies are stuck with “Franken-software”—patched-together solutions that fail to communicate effectively. Auger is different. We integrate deeply with existing systems, use AI to automate routine processes, and deliver a cohesive user experience that feels intuitive and natural, letting your team focus on what matters: driving growth, innovation, and sustainability. A Human-Centered Approach Broken supply chains don’t just impact businesses—they affect people. Delays mean products don’t reach shelves, miscommunications lead to overtime and burnout, and inefficiencies drive up costs and contribute to a growing carbon footprint. We believe supply chain problems are human problems, and we’re here to solve them. At Auger, we’re on a mission to make global supply chains more efficient, more sustainable, and ultimately, better for everyone.