Lead Data Scientist

Staff Data Scientist | Series A | VC - Backed AI Startup | Defense | Maritime Intelligence | The Company We’re partnering with ahigh-profile, Series A, VC-backed AI startupbuilding the next generation ofdefense and maritime intelligence infrastructure . This team is developing aglobal sensor constellation powered by proprietary AI and robotics— delivering real-time visibility into maritime activity at a scale that hasn’t existed before. The Product Their platform deployssmart edge-compute systemsacross fishing vessels and maritime fleets worldwide — collectingvideo, GPS, and multi-modal sensor datain real time. That data is ingested, processed, and surfaced through a customer-facing platform — powering insights acrossillegal fishing detection, smuggling prevention, and maritime safety . Under the hood: Distributed IoT systems at global scale Complex data pipelines acrossAWS + Azure (including gov cloud) Real-time analytics + secure API infrastructure High-stakes environments with strict compliance requirements Why This Role Matters This isn’t another dashboarding role. As aStaff Data Scientist , you’ll sit at the core of the platform — turningmassive, messy, high-dimensional sensor dataintoreal-world intelligence . You’ll also play a critical role in buildingfeedback loops for edge-deployed AI systems , directly improving how models perform in the wild. Why You Should Join? Mission-driven impact— your work directly contributes to global security and saving lives at sea True 0→1 ownership— shape analytics architecture and influence product direction Cutting-edge problems— multi-sensor, time-series, geospatial data at scale Growth stage— strong revenue momentum + real product traction Flexible career path— stay as a high-impact IC or grow into leadership What You’ll Do Analyze large-scale, real-world sensor data to uncoverpatterns, anomalies, and insights Buildscalable analytics pipelinespowering customer-facing intelligence products Partner with product + customer teams to translatecomplex operational problems into data solutions Identifymodel drift, failure modes, and performance gapsacross deployed AI systems Design feedback loops forcontinuous learning and model improvement Build internal tools forvisualization, experimentation, and metric tracking Define and refine metrics for evaluatingAI perception and detection systems Ensuredata quality, integrity, and reliabilityacross the pipeline What They’re Looking For 10+ yearsin applied data science, shipping production-grade systems StrongPython + SQLskills (pandas, numpy, scikit-learn) Experience withtime-series, geospatial, or multi-sensor data Deep understanding ofstatistical modeling(clustering, regression, anomaly detection) Familiarity withML ops(dataset versioning, labeling workflows, monitoring) Strong communicator — able to translate complex data into actionable insights Bonus: Experience working withedge AI systemsor inmaritime, aerospace, or automotive domains Tech Stack Python, pandas, numpy, scikit-learn, SQL The Team High-ownership, high-ambiguity environment — you’ll be expected to lead without a playbook Lean, mission-driven team whereengineers own outcomes end-to-end Fast-moving — ideas get shipped, not parked Strong builder culture:“you build it, you run it” Hybrid but hands-on — expect meaningful in-office collaboration Who This Is Perfect For? You’ve operated atStaff/Principal leveland want real ownership You enjoymessy, real-world data problems , not just clean datasets You want your work to matter beyond dashboards —real-world impact Join a team turning cutting-edge AI into real-world impact — where your work shapes global security, not just dashboards