Engineer III - Forward Deployed

PODS • Clearwater, FL

5h • Onsite

About The Position

PODS operations already run on data and deep operational expertise. Operations Data Science & AI is a new team, and its mission is to encode that expertise into automated, optimized decision systems that run continuously across the network. Good models are only half of it. A forecast or an optimization changes nothing until someone can act on it inside the workflow they already use, and closing that gap is this role. As a Forward Deployed Engineer, you will report to the Director, Operations Data Science & AI and partner with data scientists, IT, and operational stakeholders to build the applications those systems run on, across demand planning, routing, scheduling, capacity planning, and resource allocation. You will be expected to move quickly from problem to working solution, and to build tools that are reliable, easy to use, and able to grow with the business.

Requirements

• Python application development: Strong Python software development skills with experience building maintainable applications around data, analytical models, and business workflows.
• Rapid application development: Ability to move quickly from problem to working solution using lightweight frameworks, reusable components, and modern development tools, including AI-assisted development tools where appropriate.
• Data and systems integration: Strong SQL skills and experience connecting applications to databases, APIs, cloud data platforms, and other enterprise systems.
• Production engineering: Experience testing, deploying, monitoring, and supporting applications in a production environment, with sound judgment about when additional engineering rigor is needed.
• Data visualization and user experience: Ability to turn complex data and model outputs into clear, intuitive interfaces and visualizations that help users make decisions.
• User-centered problem solving: Ability to work directly with operational stakeholders, understand how decisions are made, and translate business needs into practical technical solutions.
• Communication and documentation: Ability to explain technical concepts, tradeoffs, and solutions clearly and document work so that applications can be maintained and supported.
• Structure amid ambiguity: Ability to take loosely defined operational problems, determine what is needed, and independently move from concept through implementation.
• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Engineering, or a related technical field required; master’s degree preferred.
• 4+ years of software development experience, including experience building data-intensive applications, internal tools, or analytical applications.
• Strong hands-on experience with Python and SQL, including developing applications that interact with databases, APIs, and analytical models.
• Experience rapidly building and deploying data-intensive applications or decision-support tools, selecting technologies based on speed, user needs, and maintainability.
• Experience with modern software development practices including Git, testing, CI/CD, and containerization.

Nice To Haves

• Experience working with data science, analytics, machine learning, or optimization solutions is preferred.
• Experience supporting Operations, Supply Chain, logistics, transportation, or another operationally complex business is a plus.
• Experience using AI-assisted development tools to accelerate software development, testing, debugging, and documentation is a plus.

Responsibilities

• Build operational decision tools: Develop internal applications that turn forecasting, optimization, simulation, and analytical outputs into practical tools for Operations. Work directly with operational stakeholders to understand how decisions are made and translate those needs into simple, effective workflows.
• Productionize data science solutions: Partner with data scientists and IT to move models and analytical solutions from prototypes into reliable applications used by the business. Connect applications to operational data, databases, APIs, and other systems needed to support end-to-end workflows.
• Deliver and iterate quickly: Build working solutions quickly, get them in front of users, and improve them based on feedback and observed usage. Balance speed, usability, and engineering quality based on the needs and maturity of each solution.
• Build reusable tools and foundations: Develop shared components, patterns, and frameworks that make new applications faster to build and easier to maintain. Help create consistency across Operations tools so they can evolve into a connected set of decision systems.
• Deploy and support applications: Own application development and partner with IT on deployment, monitoring, security, and ongoing support. Troubleshoot issues and improve performance, reliability, and usability as adoption grows.
• Document and communicate clearly: Document application logic, architecture, workflows, and dependencies so solutions can be maintained and supported. Communicate progress, tradeoffs, and technical considerations clearly to data scientists, operational stakeholders, and technology partners.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level