Data Scientist

KDA Consulting IncHerndon, VA

About The Position

KDA Consulting Inc. is seeking a highly skilled Data Scientist with AI/ML expertise to support mission-critical programs within the Intelligence Community (IC). This role will focus on leveraging advanced analytics, machine learning, and artificial intelligence to extract insights from large, complex datasets and support data-driven decision-making. The ideal candidate will have a strong foundation in statistical analysis, machine learning model development, and data visualization, along with the ability to translate complex findings into actionable insights for both technical and non-technical stakeholders.

Requirements

  • Active TS/SCI W/ Polygraph Required.
  • Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience)
  • Strong experience in data science, machine learning, and statistical analysis
  • Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
  • Experience analyzing and working with large-scale datasets
  • Strong understanding of statistical modeling, probability, and data analysis techniques
  • Experience with data visualization tools and communicating insights effectively
  • Strong problem-solving skills and ability to work in complex, mission-driven environments

Responsibilities

  • Design, develop, and deploy machine learning models to solve complex mission problems
  • Build predictive and prescriptive analytics solutions to support operational and strategic decision-making
  • Evaluate model performance and continuously improve algorithms through testing and tuning
  • Analyze large, structured and unstructured datasets to identify trends, patterns, and anomalies
  • Perform data cleansing, feature engineering, and transformation to prepare data for modeling
  • Apply statistical techniques to validate hypotheses and support analytical findings
  • Develop dashboards, visualizations, and reports using tools such as Tableau, Power BI, or Python visualization libraries
  • Communicate insights and recommendations clearly to both technical teams and senior leadership
  • Translate complex analytical results into actionable business or mission outcomes
  • Collaborate with data engineers and software developers to operationalize models into production environments
  • Integrate machine learning solutions into enterprise systems and workflows
  • Support cloud-based model deployment in environments such as AWS or Azure
  • Work closely with cross-functional teams including engineers, analysts, and mission stakeholders
  • Participate in Agile processes including sprint planning, stand-ups, and retrospectives
  • Contribute to continuous improvement of data science methodologies and processes
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