Senior Data Scientist

Job description

In a world of possibilities, pursue one with endless opportunities. Imagine Next! At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what’s possible. Job Description: Parsons is seeking a Senior Data Scientist to support our cutting-edge Drone Armor counter-unmanned aerial systems (C-UAS) program. This role provides professional scientific data engineering and data science, requiring the application of data and engineering sciences, mathematics, and electronic phenomena to design, implement, and optimize data-centric capabilities. The Senior Data Scientist will focus on software coding, data interoperability, cloud technology, data mesh, and data tagging to enable advanced analytics, decision-support, and mission effectiveness. What You'll Be Doing 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 Mesh • Design 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 Education • Master’s degree in Computer Science, Electronics Engineering, or other engineering or technical discipline is required OR • 8 years of relevant experience in data science, data engineering, or related fields may be substituted for education Experience • Experience 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