Data Scientist (Multiple Levels)

Noblis•Washington, DC

About The Position

We are seeking highly qualified Subject Matter Experts (SMEs) across multiple levels (I–V) to support data science, aviation, engineering, psychological, analytical, and technical programs within the Federal Aviation Administration (FAA) or related federal initiatives. SMEs will apply advanced knowledge in their respective technical or analytical disciplines—particularly data science, machine learning, and data-driven analysis—to solve complex problems, integrate requirements, and contribute to system design, program execution, and organizational effectiveness. SMEs will participate in multidisciplinary teams, utilizing advanced analytical tools, simulation environments, laboratories, data analysis platforms, and test facilities. They will provide guidance in technical planning, data strategy, process improvement, and performance evaluation, ensuring that data-driven insights inform program and mission outcomes.

Requirements

U.S. citizen or green card permanent resident (3+ years U.S. residency)
Ability to obtain and maintain FAA Sutiability/Public Trust.
Experience with FAA and the environment.
Level I Required Qualifications
Bachelor’s degree in engineering, science, or related field and 4+ years of relevant experience; or equivalent aviation-related experience with 6+ years.
Level II Required Qualifications:
Bachelor’s degree in engineering, science, or related field and 8+ years of relevant experience; or equivalent aviation-related experience with 12+ years.
Level III Required Qualifications:
Master’s degree in engineering, science, or related field and 10+ years of experience; or Bachelor’s degree with 12+ years of experience.
Level IV Required Qualifications:
Master’s degree in engineering, science, or related field and 13+ years of experience; or Bachelor’s degree with 17+ years of experience.
Level V Required Qualifications:
Doctorate degree in psychology, industrial/organizational psychology, engineering, science, or related technical/analytical field and 10+ years of experience; or Master’s degree with 12+ years, or Bachelor’s degree with 17+ years of experience.

Nice To Haves

Demonstrated experience in data science, machine learning, statistics, or quantitative analysis, preferably in aviation, engineering, or related technical domains.
Proficiency with data science tools and programming languages (e.g., Python, R, SQL, TensorFlow, PyTorch, scikit-learn, Tableau, Power BI).
Strong understanding of data pipelines, data governance, and analytical model deployment in operational environments.
Ability to translate complex technical and analytical concepts into actionable insights for diverse stakeholders.
Level I
Experience with technical problem-solving, system integration, or engineering team support in aviation-related programs.
Level II
Demonstrated experience leading small technical teams, performing process improvement, and applying engineering/scientific tools to complex problems.
Level III
Experience in advanced technical planning, integration of complex systems, and use of data analysis and test facilities for problem resolution.
Level IV
Proven record of technical leadership, mentorship of junior SMEs, and contributions to program or organizational strategy.
Experience with large-scale program integration, advanced modeling, simulation, or laboratory testing.
Level V
Expertise in psychological, organizational, technical, or analytical domains applied to aviation, engineering, or large-scale program environments.
Demonstrated leadership in multidisciplinary teams, system-of-systems problem solving, and organizational planning.
Experience applying human factors, industrial/organizational psychology, or advanced analytics to improve performance, safety, and process outcomes.

Responsibilities

Apply advanced knowledge in data science, engineering, psychology, or related technical disciplines to solve complex technical or organizational problems within the FAA or similar environments.
Extract insights and value from large and complex datasets to inform decision-making, enhance system performance, and drive innovation across programs.
Develop and implement data-driven solutions and predictive models using advanced statistical, machine learning, and data analysis techniques.
Collect, clean, and integrate data from multiple sources to support analytical, technical, and operational objectives.
Perform exploratory data analysis (EDA) to identify trends, patterns, and relationships in data relevant to aviation safety, engineering performance, human factors, or organizational outcomes.
Utilize scientific, engineering, and analytical tools (e.g., Python, R, SQL, MATLAB, data visualization platforms) to design, test, and validate analytical models and simulations.
Collaborate with cross-functional teams—including software engineers, data analysts, behavioral scientists, and domain experts—to integrate data science solutions into operational systems and decision-support workflows.
Develop and review technical documentation, reports, and data-driven recommendations to support program planning, compliance, and strategic decisions.
Communicate analytical findings and technical insights to stakeholders in a clear, actionable manner, enabling evidence-based decision-making.
Contribute to technical planning, data infrastructure design, and process optimization, ensuring alignment with program goals and federal data standards.
Mentor junior staff and provide expertise in data science methodologies, enhancing team capabilities and promoting a culture of analytical excellence.

Benefits

health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, and work-life programs

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