The alarm system for e-commerce operations.
Our mission is to detect and disrupt the risks - from delivery fraud to "Item Not Received" (INR) claims - that create friction between merchants, carriers, and 3PLs. We sit at the intersection of e-commerce, logistics, and fraud, turning massive, complex data streams into the clear-cut intelligence our clients need to operate safely.
We're currently a lean, high-impact pod. We are now looking for a new member: the strategic data scientist who will build and own our entire risk-detection brain.
Architect of our risk-detection brain.
As our Founding Data Scientist, you will be the architect of our intelligence function. This isn't a role for maintaining dashboards - this is a greenfield opportunity to design our risk-detection engine from the ground up.
You will be the strategic partner to the team, defining what questions we ask, what patterns we hunt for, and how we measure risk at scale. Your challenge is to take raw, high-volume data from sources like carriers and merchants and build the models that are our core product.
You will be the leader who sets the rhythm for our analytical work and mentors our growing team, turning your insights into automated, end-to-end solutions.
Own it end to end.
Define and drive the entire risk, fraud, and intelligence roadmap in close partnership with the founding team.
From framing the right questions and sourcing data to building, deploying, and monitoring production-grade ML models.
Build the measurement frameworks, statistical baselines, and core metrics to quantify risk across the entire e-commerce ecosystem.
Analyze complex, high-dimensional logistics and transactional data to uncover novel fraud vectors and anomalous behaviors.
Go beyond notebooks. Build clean, automated data pipelines and systems that run in a production environment.
Be the internal expert who translates complex findings into clear actions and product strategy.
You are driven to understand the human behaviors and systemic flaws that the data represents.
Sound like this.
4+ years of experience in data science, preferably in a high-stakes domain like fraud, risk, logistics, or fintech.
Fluent in Python and SQL with hands-on experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
A strong statistical foundation - comfortable with inference, probability, and concepts like rare-event estimation, which is critical for fraud detection.
Obsessively curious and resilient. You know the first answer is often not the right answer and get energized when a problem gets tough.
A builder who shows, not tells. You prove how good you are by shipping elegant, working solutions.
Thrives on autonomy and ownership. You want guidance, not guardrails.
A listener and a collaborator. You know the best ideas come from group conversations and you're eager to build a common vision with a small, brilliant team.
Small team. Hard problems.
We are a small team of passionate, curious people dedicated to solving hard problems. Our culture is our foundation.
We give you the freedom, trust, and tools to build end-to-end solutions.
We're critical thinkers who obsess over the details. The best solution is rarely the first one.
Everyone talks to everyone. Your voice and your ideas are critical from day one.
We are building the best infrastructure for our team to create their best work.
Ready to build?
If you are a curious, resilient builder who wants to own a core part of a new product, we would love to talk.
Apply now →
