DecisionPoint is seeking a Data Scientist to develop advanced analytics, machine learning models, and predictive capabilities that support operational visibility and decision-making in a federal/DoD-aligned mission environment. The role analyzes operational, engineering, and IT data to build anomaly-detection models, performance forecasting, predictive insights, and automated root-cause detection workflows. The Data Scientist collaborates with the dashboard team, operations and engineering teams, developers, and PMO leadership to design experiments, validate models, and produce actionable insights that feed enterprise dashboards and drive optimization opportunities. This is a fully remote position. Responsibilities include building ML models for anomaly detection, performance forecasting, trend prediction, and automated root-cause analysis; analyzing data from diverse mission systems to identify patterns and optimization opportunities; developing predictive models for uptime forecasting and incident prediction; conducting statistical analyses, A/B testing, and experimental design; integrating ML-driven insights into executive-facing dashboards; developing data pipelines, transformations, and preprocessing workflows; collaborating with subject-matter experts and system owners to understand domain data and indicators; producing data stories, visualizations, and documentation of analytical methods; recommending improvements to monitoring tools, data collection practices, and performance KPIs; and ensuring analytic outputs align with federal, DoD, and program data governance an

DecisionPoint is seeking a Data Scientist to develop advanced analytics, machine learning models, and predictive capabilities that support operational visibility and decision-making in a federal/DoD-aligned mission environment. The role analyzes operational, engineering, and IT data to build anomaly-detection models, performance forecasting, predictive insights, and automated root-cause detection workflows. The Data Scientist collaborates with the dashboard team, operations and engineering teams, developers, and PMO leadership to design experiments, validate models, and produce actionable insights that feed enterprise dashboards and drive optimization opportunities. This is a fully remote position. Responsibilities include building ML models for anomaly detection, performance forecasting, trend prediction, and automated root-cause analysis; analyzing data from diverse mission systems to identify patterns and optimization opportunities; developing predictive models for uptime forecasting and incident prediction; conducting statistical analyses, A/B testing, and experimental design; integrating ML-driven insights into executive-facing dashboards; developing data pipelines, transformations, and preprocessing workflows; collaborating with subject-matter experts and system owners to understand domain data and indicators; producing data stories, visualizations, and documentation of analytical methods; recommending improvements to monitoring tools, data collection practices, and performance KPIs; and ensuring analytic outputs align with federal, DoD, and program data governance an