Data Scientist

KDA CONSULTING INC; McLean (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

KDA Consulting Inc is seeking a Data Scientist with AI/ML expertise to support mission-critical IC programs. You will leverage advanced analytics to extract insights from large datasets and support data-driven decisions.

The role requires strong skills in statistical analysis, ML model development, and data visualization, with the ability to translate findings for technical and non-technical stakeholders. Collaboration with engineers and analysts is expected in an Agile setting.

Qualifications

• Active TS/SCI with polygraph required.
• Bachelor's degree in Data Science, CS, Math, Stats, or related field (or equivalent experience).
• Strong experience in data science, machine learning, and statistical analysis.
• Proficiency in Python and 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 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 decision-making.
• Evaluate model performance and tune algorithms.

Skills

Statistical analysis

Machine learning

Data visualization

Data analysis

Problem solving

Education

Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or related field

Tools

Python

TensorFlow

PyTorch

Scikit-learn

Tableau/Power BI

Job description

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.

Machine Learning & AI Development

• 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

Data Analysis & Exploration

• 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

Data Visualization & Communication

• 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

Model Deployment & Integration

• 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

Collaboration & Agile Delivery

• 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

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.