Senior Data Scientist
$112,200.00 - $196,400.00
ApplySenior Data Scientist
Posted 17 days ago
SENIORITY
Lead
SALARY
$112,200.00 - $196,400.00
About the role
- Data Science, Analytics & Modeling
- Design and implement data science workflows and analytics to support C-UAS detection, tracking, classification, and decision-support
- Develop and apply statistical, machine learning, and optimization techniques to extract insight from multi-source sensor, RF, telemetry, and operational data
- Build, evaluate, and refine models for anomaly detection, threat assessment, and system performance prediction in real-time or near-real-time environments
- Translate mission and system requirements into data-driven approaches, metrics, and analytic products consumable by operators, engineers, and leadership
- Data Engineering, Interoperability & Data MeshDesign and implement data pipelines for ingestion, transformation, enrichment, and distribution of data across a data mesh architecture
- Engineer data interoperability solutions across heterogeneous systems, sensors, and platforms, using common data models, schemas, and open standards where appropriate
- Collaborate on the design and implementation of a data mesh or data fabric for Drone Armor, enabling discoverable, shareable, and governed data products across teams and systems
- Ensure data solutions are robust, secure, maintainable, and aligned with program architecture, performance, and interoperability standards
- Cloud Technology & Data Platforms
- Architect and implement data pipelines, storage, and analytics capabilities in cloud or hybrid environments (e.g., commercial, tactical, or private cloud)
- Leverage cloud-native services and technologies for scalable data processing, streaming, and model deployment
- Optimize data and analytics workloads for resilience, performance, and cost within cloud-based infrastructures
- Integrate on-premise, edge, and cloud components into cohesive end-to-end data and analytics solutions for mission operations
- Data Tagging, Governance & Quality
- Design and implement data tagging strategies (e.g., metadata, security labels, lineage tags) to support discoverability, access control, and policy compliance
- Define and enforce data quality metrics, validation rules, and monitoring to ensure the reliability of analytics and downstream decision-making
- Work with stakeholders to establish data governance practices, including data cataloging, classification, and lifecycle management
- Support the creation of well-documented, reusable data products and datasets within the data mesh
- Collaboration, Visualization & Communication
- Work closely with systems engineers, RF engineers, software developers, and operators to understand mission needs and translate them into data and analytics requirements
- Develop visualizations, dashboards, and analytic reports that clearly communicate complex findings to both technical and non-technical audiences
- Mentor junior data scientists and data engineers, providing technical guidance on methods, tools, and best practices
- Contribute to technical reviews, design walkthroughs, and continuous improvement of data science and data engineering practices
- What Required Skills You'll Bring
- EducationMaster's degree in Computer Science, Electronics Engineering, or other engineering or technical discipline is requiredOR8 years of relevant experience in data science, data engineering, or related fields may be substituted for education
- ExperienceExperience applying data and engineering sciences, mathematics, and electronic phenomena to real-world systems or mission problems
- Experience designing and implementing data pipelines and data interoperability solutions in complex, multi-system environments
- Experience with cloud-based or hybrid data and analytics solutions, including data storage, processing, and model deployment
- Experience working with data mesh or similar distributed data architectures, including data product design and governance
- Experience with data tagging, metadata management, and data cataloging to support discoverability, security, and compliance
- Experience reacting to and resolving data-related issues (e.g., quality, latency, integrity, model performance) in complex or mission-critical systems
- Technical Competencies
- Proficiency in one or more languages commonly used for data science and data engineering (e.g., Python, R, Scala, or similar), including use of relevant libraries and frameworks
- Strong understanding of data engineering concepts: ETL/ELT, streaming, batch processing, APIs, and event-driven data flows
- Familiarity with cloud data and analytics services (e.g., managed databases, data lakes, streaming services, containerized processing)
- Knowledge of data modeling, schemas, and standards used in sensor, RF, telemetry, or ISR/C2 environments is a plus
- Strong analytical and communication skills, capable of explaining complex data and model behavior, trade-offs, and limitations to both technical and non-technical stakeholders
- Security & Citizenship
- Must be a US Citizen
- Ability to obtain and maintain a security clearance (SECRET or higher; specific level may be defined by program requirements)
- What Desired Skills You'll Bring
- Advanced Education & Certifications
- Master's or higher degree in Data Science, Computer Science, Electrical/Electronics Engineering, or related discipline
- Professional certifications in cloud platforms, data engineering, or data science/MLSpecialized Experience
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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