Staff Data Scientist — Defense AI / Sensor Intelligence (Only US Citizen)
location: Hybrid in Arlington, VA or remote in Boston, the Bay Area, San Diego, or Los Angeles. Another office outside of Arlington may be established in the near future.
Compensation:$260k+ with Equity
preffered :U.S. Defense / Government Experience defense-domain
Candidates without defense-domain experience are unlikely to be considered.
We are hiring a Staff Data Scientist to help build next-generation AI systems powering mission-critical defense and sensor intelligence platforms.
Quartermaster specializes in placing sensors on boats to monitor ocean activity, detecting illegal fishing and smuggling.
This role is focused on transforming large-scale operational and sensor data into actionable intelligence through advanced machine learning, anomaly detection, experimentation systems, and scalable analytics infrastructure.
We are specifically seeking candidates with direct experience in:
- defense technology
- aerospace & defense
- military systems
- intelligence platforms
- cyber defense
- autonomous systems
- government / DoD environments
What You’ll Work On
- Build advanced analytics and intelligence systems for operational deployments
- Develop anomaly detection, predictive modeling, and monitoring frameworks
- Design scalable ML pipelines for structured and unstructured sensor data
- Detect model drift, edge cases, and operational failures
- Support retraining workflows and dataset enrichment
- Build experimentation, visualization, and operational analytics platforms
- Partner with engineering, product, and mission teams to deploy production AI systems
- Improve decision-making from real-world telemetry and field data
Required Qualifications
- 10+ years of applied Data Science / Machine Learning experience
- Strong experience in defense, aerospace, intelligence, cyber, or government systems
- Expert-level Python and SQL
- Strong experience with:
- pandas
- NumPy
- scikit-learn
- Spark / distributed data systems
- Deep statistical modeling and anomaly detection expertise
- Experience with:
- time-series analytics
- telemetry analytics
- multi-sensor data
- operational intelligence systems
- Experience building production ML systems end-to-end
- Experience with ML Ops, monitoring, and model lifecycle management
- Strong systems thinking and architecture ownership experience
Highly Preferred
- Experience at defense-tech or aerospace organizations such as:
- Anduril Industries
- Palantir Technologies
- Lockheed Martin
- Northrop Grumman
- Raytheon
- Shield AI
- L3Harris Technologies
- Leidos
- General Dynamics
- TS/SCI or active security clearance
- Edge AI or autonomous systems experience
- Sensor fusion or ISR systems exposure
- Cyber anomaly detection experience
- Geospatial analytics or satellite intelligence experience
- Startup or defense-tech startup background
- PhD in Computer Science, Statistics, Applied Mathematics, Physics, or related field
Technical Environment
- Python
- SQL
- Spark / Kafka
- ML Ops platforms
- Cloud infrastructure (AWS/GCP/Azure)
- Time-series analytics
- Distributed ML systems
- Monitoring & observability frameworks
- Real-time analytics pipelines
- Edge AI systems
Ideal Candidate Profile
You are:
- highly hands-on technically
- comfortable operating in ambiguous environments
- capable of owning systems end-to-end
- experienced in mission-critical production systems
- comfortable working with operational or deployment data
- capable of shipping quickly in high-performance environments
Defense AI | Sensor Intelligence | ISR | Telemetry Analytics | Edge AI | Mission Systems | Autonomous Systems | Anomaly Detection | ML Ops | Time Series | Cyber Analytics | Defense-Tech | DoD | TS/SCI | Sensor Fusion | Operational Intelligence | Real-Time Analytics | Geospatial Analytics | Distributed ML Systems
Pay: From $260,000.00 per year
Application Question(s):
- How many years of Defense and Space Manufacturing experience do you currently have? (10+) Required
- Your Current Compensation?
Expected Compensation ?
- Are you U.S Citizen ? (Mandatory) (Yes/No)
- Experience in translating raw data into production insights/tools within geospatial intelligence, maritime, defense tech, or adjacent regulated/government-adjacent industries ? (Yes/No)
- Do you posses 10+ years of experience in applied data science, with a track record of translating raw data into production insights or tools. (Mention Years)
Education:
Experience:
- Machine learning: 10 years (Required)
- Defense and Space Manufacturing: 5 years (Required)
- Applied Data Science: 10 years (Required)
Work Location: Hybrid remote in Arlington, VA (Arlington County)
