Protect our Land, Ascend with Us!

Ascension LLC is seeking a GIS Data Scientist / Geospatial Analyst to support a federal data analytics and application support services effort for the Department of War Office of Inspector General’s Analytics Team within Mission Support. This role will help the customer transform complex operational, oversight, and investigative data into location-based insights that support audits, evaluations, investigations, and mission decision-making.

The ideal candidate is a technically strong, mission-focused analyst who can combine data science methods with geospatial analysis, GIS visualization, statistical reasoning, and clear communication. This position requires someone who can work with structured and unstructured data, integrate geospatial and non-geospatial datasets, identify spatial patterns and anomalies, develop map-based visualizations, and explain methods and findings to both technical and non-technical stakeholders.

This role is important because the customer’s mission depends on timely identification of patterns, trends, anomalies, and risks that may indicate fraud, waste, abuse, operational inefficiencies, or other issues requiring oversight attention. The PWS specifically requires geospatial analytics services to analyze spatial relationships, identify location-based patterns and trends, create maps and visualizations, perform proximity analysis, integrate geographic data with other data sources, and document data provenance and limitations.

Summary of Contractor Role

The GIS Data Scientist / Geospatial Analyst will support advanced analytics and geospatial analysis activities across the customer’s analytics environment. The role will contribute to analytical planning, data preparation, statistical analysis, model development, geospatial visualization, and documentation. The candidate will be expected to apply appropriate analytical methods, validate assumptions, explain limitations, and ensure that outputs are accurate, repeatable, accessible, and aligned with federal quality standards.

The position requires a detail-oriented, self-driven professional who can operate in a complex federal mission environment with limited supervision. The successful candidate should be comfortable working in iterative development cycles, collaborating with data scientists, business intelligence analysts, data engineers, project managers, and customer stakeholders. The candidate should also be skilled at turning ambiguous mission questions into well-defined analytical tasks, building repeatable workflows, and developing products that help the customer act on data with confidence.

Tools and processes may include ArcGIS Pro, ArcGIS Online or Enterprise, Python, SQL, R, Jupyter Notebooks, Power BI, Tableau, Azure DevOps, SharePoint, Git or other version control tools, data quality review processes, geospatial data governance, model documentation, knowledge transfer materials, and technical reporting. The PWS also emphasizes documentation, knowledge transfer, sustainment, and formal acceptance of analytics products.

Anticipated Day-to-Day Activities

• Analyze spatial relationships, geographic patterns, location-based risks, proximity relationships, and trends across mission-relevant datasets.
• Develop geospatial analysis plans, analytical workflows, maps, dashboards, reports, and visual products that support audits, evaluations, investigations, and oversight activities.
• Integrate GIS data with operational, programmatic, financial, investigative, or administrative datasets to support broader analytics use cases.
• Perform data cleaning, transformation, geocoding, spatial joins, feature engineering, and exploratory spatial data analysis.
• Apply statistical and data science methods, including regression, clustering, anomaly detection, classification, predictive analytics, and trend analysis, where appropriate.
• Create clear maps, visualizations, and location intelligence products that communicate findings to technical and non-technical audiences.
• Document methodologies, assumptions, data sources, data lineage, limitations, validation steps, and analytical conclusions.
• Use authoritative and current geospatial data sources and maintain clear records of data provenance, quality, and constraints.
• Collaborate with data engineers and BI analysts to ensure geospatial datasets are structured, accessible, and usable for dashboards and advanced analytics.
• Support model lifecycle activities, including testing, validation, monitoring, retraining recommendations, version control, and governance documentation.
• Prepare findings reports, technical briefs, user guides, and knowledge transfer materials.
• Participate in stakeholder meetings, requirements discussions, peer reviews, and solution demonstrations.
• Recommend improvements to geospatial workflows, analytics methods, data quality controls, and repeatable reporting processes.
• Maintain files, documentation, assumptions, and analytical outputs in designated repositories such as SharePoint, Azure DevOps, or other approved systems.
• Support sustainment activities by updating documentation, refresh procedures, and maintenance instructions for deployed analytical products.