OverviewDecisionPoint seeks a Data Scientist to develop advanced analytics, machine learning models, and predictive capabilities that support operational visibility and decision-making across a large federal and DoD-aligned mission environment. This role analyzes operational, engineering, and IT datasets to build anomaly detection models, performance forecasting algorithms, predictive insights, and automated root-cause detection workflows.
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.
This position is fully remote.
Duties & Responsibilities
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.
Qualifications
Clearance Requirement
Candidate must possess a Tier 2 Moderate Risk Public Trust (from any federal agency) or an active Secret clearance or higher.
Education (Required)
Bachelors 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:
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.
