Data Scientist – Mid

GRVTY•Springfield, VA

About The Position

We are seeking a Mid-Level Data Scientist to provide embedded automation and GEOINT integration support. In this role, you will design and implement automation and augmentation capabilities that connect databases, applications, and enterprise systems to reduce manual effort, improve data accessibility, and accelerate production workflows. Your work will directly support NGA modernization initiatives. By integrating disparate data sources and automating repetitive tasks, you will help ensure analysts and decision-makers have timely access to the information they need to support mission execution. You will work side by side with GEOINT analysts, database developers, and government stakeholders to identify inefficiencies, develop scalable solutions, and sustain modernized workflows. Success in this position requires a combination of GEOINT awareness, automation expertise, database integration experience, and strong technical problem-solving skills. Your contributions will improve operational efficiency, enhance data management practices, and ensure continuity of products and services delivered.

Requirements

Active TS/SCI clearance with the ability to obtain and maintain a CI Polygraph.
9+ years of relevant experience in data science, automation, software development, data engineering, database integration, GEOINT support, or related technical disciplines. A combination of education, professional certifications, and technical training may be considered in lieu of some years of experience.
Proficiency in Python and its data science and visualization ecosystem, including Pandas, NumPy, SciPy, Matplotlib, Plotly, Dash, Bokeh, and related libraries.
Demonstrated experience connecting multiple databases and enterprise systems to automate data collection, transformation, and dissemination.
Experience automating repetitive business or analytic tasks using scripts and workflows.
Experience gathering and disseminating metrics and operational data.
Demonstrated ability to identify process inefficiencies and implement automation solutions that improve workflow performance.
Strong analytical and problem-solving skills.
Effective written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.

Nice To Haves

Basic understanding of GEOINT workflows, including collection, exploitation, analysis, and product delivery.
Experience with workflow management systems such as Flowable or Esri Workflow Manager.
Experience supporting National Geospatial-Intelligence Agency or other Intelligence Community organizations.
Experience working with modernized database applications and enterprise APIs.
Bachelor’s or Master’s degree in Computer Science, Data Science, Geographic Information Systems, Engineering, Information Systems, or a related technical discipline.

Responsibilities

Provide embedded GEOINT, automation, and augmentation expertise to ensure continuity of products and services delivered to the National System for Geospatial-Intelligence (NSG).
Develop automation solutions that connect databases and enterprise systems to streamline production and requirements workflows.
Integrate and transform data from multiple sources to collect, assemble, and prepare information for finished products and operational decision-making.
Gather, store, and disseminate metrics, operational data, and performance information between local and enterprise systems.
Research existing SFP data management practices and help design modernized workflows to improve efficiency and consistency across programs.
Ensure workflows integrate seamlessly with modernized database applications and enterprise APIs.
Automate repetitive data management and reporting tasks to reduce manual effort and improve accuracy.
Develop algorithms and scripts using Python and related technologies to support data processing and workflow automation.
Utilize Esri ArcGIS Pro, ArcSDE, and related Esri tools to support data discovery, analysis, and integration activities.