{"id":802026,"url":"https://alion.io/job/kda-consulting-data-scientist","title":"Data Scientist","company":{"id":679205,"name":"KDA Consulting","domain":"kda-consulting.com","url":"https://alion.io/company/kda-consulting","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chantilly, United States","Herndon, United States","McLean, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":110000,"max_usd":239000,"period":"year","method":"role_country_seniority_unknown","sample_n":3718},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Tableau","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-04-05T00:00:00Z","employer_posted_date":"2026-04-05","last_verified_at":"2026-11-07T16:21:02Z","board_verified":true,"closed_at":null,"days_open":216,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":216},"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.\nThe 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.\nMachine Learning & AI Development\n Design, develop, and deploy machine learning models to solve complex mission problems \n Build predictive and prescriptive analytics solutions to support operational and strategic decision-making \n Evaluate model performance and continuously improve algorithms through testing and tuning \nData Analysis & Exploration\n Analyze large, structured and unstructured datasets to identify trends, patterns, and anomalies \n Perform data cleansing, feature engineering, and transformation to prepare data for modeling \n Apply statistical techniques to validate hypotheses and support analytical findings \nData Visualization & Communication\n Develop dashboards, visualizations, and reports using tools such as Tableau, Power BI, or Python visualization libraries \n Communicate insights and recommendations clearly to both technical teams and senior leadership \n Translate complex analytical results into actionable business or mission outcomes \nModel Deployment & Integration\n Collaborate with data engineers and software developers to operationalize models into production environments \n Integrate machine learning solutions into enterprise systems and workflows \n Support cloud-based model deployment in environments such as AWS or Azure \nCollaboration & Agile Delivery\n Work closely with cross-functional teams including engineers, analysts, and mission stakeholders \n Participate in Agile processes including sprint planning, stand-ups, and retrospectives \n Contribute to continuous improvement of data science methodologies and processes\nRequirements\nActive TS/SCI W/ Polygraph Required.\nBachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (or equivalent experience)\nStrong experience in data science, machine learning, and statistical analysis\nProficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn\nExperience analyzing and working with large-scale datasets\nStrong understanding of statistical modeling, probability, and data analysis techniques\nExperience with data visualization tools and communicating insights effectively\nStrong problem-solving skills and ability to work in complex, mission-driven 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