Data Scientist

Master our Data: Get deeply familiar with our data: where it comes from, how it’s generated, and why it exists.

Hunt for Signals: Explore raw, imperfect datasets to find patterns, anomalies, and fraud signals that others miss.

Guide Strategy: Build analyses that help us understand trends and decide what signals or models to build next.

Build Tools: Write SQL and Python to investigate data, validate assumptions, and build small internal tools or scripts so we always know what our data looks like.

Drive Transparency: Help design and build analytics dashboards that give our customers visibility into the trust layer.

Ensure Quality: Be heavily involved in QA before new models or signal iterations go out, working closely with engineering to request better instrumentation and logging.

Technical Proficiency: Highly skilled in SQL and Python.

Query Expert: Comfortable with Elasticsearch, KQL, and DSL query languages.

Data Intuition: You thrive on messy, incomplete, real-world data and enjoy building tools from scratch to tame it.

Curious & Skeptical: You are detail-oriented and care deeply about correctness and data quality; you aren't afraid to ask "why" and push for better data.

Autonomous: You thrive in ambiguity and are comfortable working without perfect specs or pre-defined roadmaps.

Collaborative: Interested in working across product, engineering, and ML teams to turn data insights into production-ready security features.

Django experience

Experience in fraud, trust & safety, or risk systems

Experience building customer-facing analytics

Familiarity with ML workflows or model evaluation

You’ll help build the trust layer for the internet, one of the defining problems of the AI era.

Work directly with a team obsessed with building a generational company.

Insane level of ownership—your analyses will directly dictate the product roadmap.