• This is a rare opportunity to define how data moves across the U.S. military’s logistics ecosystem. • As the Architecture and Data Lead, you will own one of the most critical integration challenges in modern DoD software. • You will design and build the integration platform that connects DEFCON AI’s software to the broader logistics C2 ecosystem. • This is a senior role combining deep technical execution and system-level architecture leadership.

• Partner with senior scientists to forecast cash flows and other drivers of business health using statistical and ML modeling. • Design and build models that make our capital products better for customers and deliver positive return assets. Sharper pricing, lower losses, growth and offers that fit how SMBs actually run. • Proactively mine our datasets for insight, and prototype new models that move the needle for customers and the business. • Own model outcomes end-to-end. Not just deployment bespoke to the platforms Pipe serves (e.g., UberEats and Housecall Pro), but ongoing performance, residual analysis, drift detection, and the judgment calls about when a model needs to be retrained, replaced, or retired. You'll work closely with product, risk peers and engineering to make this real in production.

• Independently developing and owning statistical models that forecast cash flows and other drivers of business and customer health. • Designing and building models that optimize our product offerings to better serve our customers' needs. • Proactively exploring datasets to surface insights, and prototyping new approaches that create measurable value for customers. • Taking full outcome ownership of deployed models, including performance monitoring, residual analysis, and iteration, in close collaboration with engineering. • Mentoring junior team members, raising the technical bar through code and design review, and contributing to our data science best practices and long-term tooling roadmap. • Partnering with engineering and data engineering to productionize models, shape data infrastructure requirements, and improve our MLOps foundations.

• Define and own the KPIs that measure CX health, downstream impact, product experience, and user sentiment. • Analyze user behavior and marketplace dynamics to identify opportunities and inform CX product and agent team priorities. • Measure the tradeoffs between user experience and business value. • Translate complex data into actionable recommendations for product and leadership teams. • Partner with product managers and engineers to design, implement, and evaluate A/B tests and feature rollouts. • Develop frameworks for causal inference, impact measurement, and long-term ecosystem health. • Build scalable methodologies to understand feature performance and guide iteration. • Use our modern data stack to build dashboards, data pipelines, and self-serve tools that empower teams across Whatnot. • Partner with engineers and operations leadership to improve data accessibility, ensure data quality, and support instrumentation for new product features. • Advocate for data-driven decision-making and foster a culture of measurement across the CX organization. • Communicate insights clearly to both technical and non-technical audiences, influencing roadmaps and strategic decisions. • Serve as a thought partner to CX leads, shaping how we build, launch, and iterate on experiences across the platform.