Mission-Critical Data Scientist: AI/ML & Analytics

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 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.