Data Scientist / Forward Deployed Engineer

ClosedWon Talent; New York (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

Atomic is hiring Forward Deployed Engineers to own customer deployments end to end. You’ll work across multiple supply chain modules, translating messy data into reliable software, and delivering fast, customized solutions.

You’ll collaborate with customers, shape optimization models, and build AI-enabled interfaces that help clients analyze and act on their plans. Expect close client interaction and hands-on engineering across the platform.

Qualifications

• Strong Python skills and ability to build automated data pipelines.
• Experience with AI tooling and modern coding tools.
• Comfortable in client-facing deployments and technical conversations.
• Experience in data engineering, planning, or related fields is a plus.

Responsibilities

• Build automated, normalized data pipelines on top of a customer's messy real-world supply chain data
• Shape optimization logic and models to how each business actually runs
• Build the interfaces and AI features customers use to interact with and analyze their plans
• Wire the platform into customer systems, ERPs, and partner platforms
• Work directly with customers on every technical conversation, translating business problems into working software

Skills

Python

Data pipelines

Client-facing

AI tooling

Tools

Claude

Job description

About the Company

Most companies still plan their supply chains, meaning quantities, mix, allocations, and timing, in spreadsheets or legacy software. The spreadsheets break as soon as the business moves quickly. The legacy suites take a year to implement and frequently lose to the spreadsheets anyway.

Atomic is rebuilding the brain behind the American supply chain. By tackling operations optimization from first principles with an AI-native stack, they deliver unprecedented results at breakneck speed for their customers. Customers include DoorDash, HelloFresh, Archer Meat Snacks, Starface World, LMNT, OOFOS, Cora, and Chomps.

The founders lived this problem before they built the solution. Michael Rossiter and Neal Suidan built Tesla's end-to-end supply chain orchestration system from scratch during the Model 3 ramp, after watching a company that size run on spreadsheets that could not keep up with how fast the business moved. Revenue has grown roughly 10x this year.

About the Role

Forward Deployed Engineers own customer deployments end to end. It's the same technical work the core engineering team does, but client-facing and embedded across the entire problem rather than scoped to one layer of it.

The engineering team builds and maintains the platform foundation. This team sits on top of it, connecting each customer to the baseline and then figuring out everything that has to happen for it to be genuinely right for that business. You'd typically be deep in one customer at a time, working across several modules of their supply chain i.e warehouse replenishment, kitting site planning, raw production, raw material purchasing, each with different stakeholders, different data, and different nuance.

The hard part isn't the code. Customers hand you data in every format and state of cleanliness, tell you what they think they need, and some of it will be wrong. Figuring out what to actually build, and building it fast, is the primary goal.

What You'll Do

• Build automated, normalized data pipelines on top of a customer's messy real-world supply chain data
• Shape optimization logic and models to how each business actually runs
• Build the interfaces and AI features customers use to interact with and analyze their plans
• Wire the platform into customer systems, ERPs, and partner platforms
• Work directly with customers on every technical conversation, translating business problems into working software

Must-Have Requirements

• 3+ years of experience for FDE, 6+ years for Sr. FDE
• Strong, current Python skills
• Daily working fluency with Claude and modern AI coding tools
• A supply chain or planning background. Adjacent paths that work well include planning, data engineering, data science, management consulting, finance, and industrial engineering, provided the supply chain exposure is real
• The ability to take thin, messy, incomplete context and still deliver an excellent outcome quickly. This is the hardest and most important part of the job
• Comfort sitting in front of customers and owning the technical relationship
• Ability to work autonomously without heavy direction, and to stay creative when the requirements are ambiguous