Über
high-profile, Series A, VC-backed AI startup
building the next generation of
defense and maritime intelligence infrastructure . This team is developing a
global 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 deploys
smart edge-compute systems
across fishing vessels and maritime fleets worldwide — collecting
video, GPS, and multi-modal sensor data
in real time. That data is ingested, processed, and surfaced through a customer-facing platform — powering insights across
illegal fishing detection, smuggling prevention, and maritime safety . Under the hood: Distributed IoT systems at global scale Complex data pipelines across
AWS + 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 a
Staff Data Scientist , you’ll sit at the core of the platform — turning
massive, messy, high-dimensional sensor data
into
real-world intelligence . You’ll also play a critical role in building
feedback 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 uncover
patterns, anomalies, and insights Build
scalable analytics pipelines
powering customer-facing intelligence products Partner with product + customer teams to translate
complex operational problems into data solutions Identify
model drift, failure modes, and performance gaps
across deployed AI systems Design feedback loops for
continuous learning and model improvement Build internal tools for
visualization, experimentation, and metric tracking Define and refine metrics for evaluating
AI perception and detection systems Ensure
data quality, integrity, and reliability
across the pipeline What They’re Looking For 10+ years
in applied data science, shipping production-grade systems Strong
Python + SQL
skills (pandas, numpy, scikit-learn) Experience with
time-series, geospatial, or multi-sensor data Deep understanding of
statistical modeling
(clustering, regression, anomaly detection) Familiarity with
ML ops
(dataset versioning, labeling workflows, monitoring) Strong communicator — able to translate complex data into actionable insights Bonus: Experience working with
edge AI systems
or in
maritime, 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 where
engineers 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 at
Staff/Principal level
and want real ownership You enjoy
messy, 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
Sprachkenntnisse
- English
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