Data Scientist

The Data Scientist collaborates closely with the dashboard team, operations and engineering teams (O&E), developers, and PMO leadership to design experiments, validate models, and produce meaningful insights that feed enterprise dashboards and drive optimization opportunities., The Data Scientist will:

• Build machine learning models for anomaly detection, performance forecasting, trend prediction, and automated root-cause analysis.

• Analyze operational, engineering, and IT data from diverse mission systems to identify patterns and optimization opportunities.

• Develop predictive models supporting uptime forecasting, incident prediction, and performance thresholds.

• Conduct statistical analysis, A/B testing, and experimental design to validate hypotheses and model outputs.

• Work closely with the Dashboard COE to integrate ML-driven insights into executive-facing dashboards.

• Develop data pipelines, transformations, and preprocessing workflows needed for ML/analytics models.

• Collaborate with SMEs and system owners to understand domain data, context, and mission-critical indicators.

• Produce data stories, visualizations, narrative explanations, and technical documentation of analytical methods.

• Recommend improvements to monitoring tools, data collection practices, and performance KPIs.

• Ensure all analytic outputs align with federal, DoD, and program data governance and security requirements.

Candidate must possess a Tier 2 Moderate Risk Public Trust (from any federal agency) or an active Secret clearance or higher.

Education (Required)

Bachelor’s degree in Data Science, Computer Science, Artificial Intelligence/Machine Learning, Statistics, or a related field.

Experience (Required)

• Minimum 7 years of experience performing data science, advanced analytics, or machine learning.

• Experience applying ML techniques such as classification, anomaly detection, regression, clustering, or time-series forecasting.

• Experience designing experiments, running statistical analyses, and validating model performance.

• Experience working with operational, engineering, or IT datasets and translating findings into actionable insights.

• Experience collaborating with dashboard teams or integrating analytical outputs into BI platforms.

Technical Knowledge (Required)

• Proficiency with Python, R, or similar languages used for statistics and machine learning.

• Strong understanding of ML algorithms, feature engineering, and model evaluation.

• Experience with SQL and data transformation pipelines.

• Familiarity with visualization tools such as Power BI, Tableau, or similar platforms.

Technical Knowledge (Preferred)

• Experience operating in cloud environments (AWS preferred).

• Familiarity with DevSecOps, automation, or CI/CD analytics integration.

• Experience with distributed computing or big data analytics frameworks.

Certifications

Required:

• ITIL v4 Foundation

Preferred:

• Data science, analytics, or ML certifications

• AWS cloud or machine learning specialty certifications

Skills

• Strong analytical and mathematical reasoning skills.

• Ability to translate complex findings into concise dashboards or executive summaries.

• Excellent problem-solving and model debugging skills.

• Strong communication and collaboration skills across technical and business teams.

• High attention to detail and commitment to model accuracy and data validity.