Senior Data Scientist (Business Operations)
Actively Hiring
Full-time $135k - $185k Posted 24 days ago
Responsibilities
- check_circle Collect, integrate, and validate COMSATCOM usage, inventory, operational, financial, and capability data from GFI, non-GFI, and other structured and unstructured data sources.
- check_circle Develop and maintain predictive models, statistical analyses, and stochastic forecasting methodologies to assess current and future COMSATCOM demand, utilization, capacity, and operational risk.
- check_circle Apply advanced analytical and AI/ML techniques — including regression, classification, clustering, anomaly detection, machine learning, deep learning, and generative AI methods — to identify trends, drivers, and decision-relevant insights.
- check_circle Leverage DoD-approved AI and generative AI platforms, including genai.mil and equivalent NIPR/SIPR AI environments, to accelerate analytical workflows and support production of executive-ready analytic products; apply responsible AI principles including bias detection, model interpretability, and assumptions documentation.
- check_circle Design and implement reproducible analytic workflows, data pipelines, and model validation processes to ensure transparency, traceability, and repeatability; partner with data engineers on pipeline operationalization and production deployment.
- check_circle Translate complex operational and business questions into analytical models, simulations, and AI/ML-enabled decision-support tools for USSF CSCO leadership and mission partners.
- check_circle Create executive-level visualizations, dashboards, and briefings that communicate complex technical and AI-generated findings to senior stakeholders in an understandable and actionable manner.
- check_circle Maintain awareness of global, regional, and situational SATCOM trends and incorporate them into forecasts, scenario analyses, and strategic assessments.
- check_circle Support analytic studies with COMSATCOM SMEs, including cost analyses, business case analyses, market research, commercial capability assessments, and courses of action comparisons.
- check_circle Develop metrics, analytical frameworks, and model-based decision aids supporting planning, portfolio management, and leadership data calls with speed, accuracy, and traceability.
- check_circle Provide technical leadership on data science best practices, AI governance, and model lifecycle management; respond to ad hoc analytic taskings from senior leadership with timely, defensible analyses.
Basic qualifications
- Minimum of 8 years of experience in data science, data analytics, operations research, computer science, economics, engineering, mathematics, statistics, or a related quantitative field.
- Bachelor's Degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Operations Research, Economics, or a related field.
- Secret Clearance required. #qinetiqclearedjob
- Demonstrated experience applying advanced statistical methods, predictive analytics, and machine learning techniques to real-world operational or business problems.
- Demonstrated experience applying or integrating AI/ML tools, including generative AI or large language model (LLM) applications, in analytic or decision-support workflows.
- Strong proficiency in Python, SQL, and data analysis libraries and tools used for data wrangling, modeling, and visualization.
- Experience developing executive-level visualizations, dashboards, and analytic briefings for senior decision-makers.
- Familiarity with responsible AI principles and model governance standards applicable to DoD or government program environments.
- Strong analytical, problem-solving, and decision-making capabilities.
- Excellent verbal and written communication skills, including the ability to explain technical and AI-generated findings to non-technical audiences.
- Deadline-driven, organized, detail-oriented, and able to operate effectively in a fast-paced environment.
- Ability to support on-site client meetings within the National Capital Region.
Preferred qualifications
- Master's Degree or higher in Data Science, Statistics, Mathematics, Computer Science, Operations Research, Engineering, or a related field.
- Experience with DoD-approved AI and generative AI platforms, including genai.mil, or equivalent NIPR/SIPR AI environments.
- Familiarity with large language model (LLM) applications, prompt engineering, and retrieval-augmented generation (RAG) techniques applied to government or defense analytic workflows.
- Experience supporting USG, USSF, DoD, or other national security space programs in analytically intensive environments.
- Familiarity with U.S. Government or DoD acquisition processes, analytic rigor standards, and mission-support decision frameworks.
- Experience with Power BI, Tableau, or similar business intelligence and visualization platforms.
- Experience with cloud-based data platforms (AWS GovCloud, Azure Government, Databricks) and ML/MLOps frameworks for model lifecycle management.
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