Data Scientist

Data Scientist With Ai/Ml ExpertiseKDA 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 DevelopmentDesign, develop, and deploy machine learning models to solve complex mission problemsBuild predictive and prescriptive analytics solutions to support operational and strategic decision-makingEvaluate model performance and continuously improve algorithms through testing and tuningData Analysis & ExplorationAnalyze large, structured and unstructured datasets to identify trends, patterns, and anomaliesPerform data cleansing, feature engineering, and transformation to prepare data for modelingApply statistical techniques to validate hypotheses and support analytical findingsData Visualization & CommunicationDevelop dashboards, visualizations, and reports using tools such as Tableau, Power BI, or Python visualization librariesCommunicate insights and recommendations clearly to both technical teams and senior leadershipTranslate complex analytical results into actionable business or mission outcomesModel Deployment & IntegrationCollaborate with data engineers and software developers to operationalize models into production environmentsIntegrate machine learning solutions into enterprise systems and workflowsSupport cloud-based model deployment in environments such as AWS or AzureCollaboration & Agile DeliveryWork closely with cross-functional teams including engineers, analysts, and mission stakeholdersParticipate in Agile processes including sprint planning, stand-ups, and retrospectivesContribute to continuous improvement of data science methodologies and processes