Data Scientist (Vantage) - Clearance Required

Overview

LMI is seeking a Data Scientist to assist with Army data model, pipeline, and visualization development. This Data Scientist will create data models working from mock visualizations and raw data inputs; leverage python, PySpark, Foundry, and code repositories to develop an architecture plan; extract, transform, and load data into Vantage; and use Vantage workshops to develop visualizations. Active Secret clearance required.

 

Location: Open to Remote. Local preferred at client site in Crystal City VA or Aberdeen MD.

 

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

 

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Responsibilities

Core Responsibilities:  

• Data Engineering: Extract, transform, and load data using big data platforms like Palantir Foundry, loading data into data visualizations, transforming data using python and low code data pipeline building tools. 

• Workflow Development: Build low-code no-code applications that allow end users to see real-time readiness dashboards. 

• Data Integration: Automate and clean the ingestion of data from legacy systems so it’s useful for decision-making. 

• Predictive Analytics: Create models to forecast equipment failures, personnel shortages, or budget overruns. 

• PI Planning: Help with feature writing, task decomposition, acceptance criteria, user stories, and processes for extracting dependencies from descriptive models. 

• Ad-Hoc Reporting: Quickly answer critical information requirements by pulling data across different domains, ability to gather customer requirements and deliver a comprehensive statistical analysis to answer their questions.  

 

General Responsibilities: 

• Support project management over data activities to ensure timely delivery in a reactive and agile environment. 

• Engage technical and functional program SMEs, and key data stakeholders to understand business processes, analytical requirements, key data elements, data protection guidelines, etc. 

• Define and develop techniques to integrate, consolidate, and structure data for analytical use. 

• Create data pipelines in python, going from raw data to data products needed for visualization or other analytics products.  

• Understand and analyze complex and organization-specific datasets. 

• Transform data and analysis into informative visualizations and interactive dashboards using open-source and commercially available visualization and dashboard tools. 

• Propose alternative designs and processes to manage various types of data using both standard and custom tables and fields. 

• Provide recommendations for improvements in data strategies to include changes to governance, stewardship, integration, and standardization. 

Qualifications

Qualifications:  

• Bachelor's degree in data science, mathematics, statistics, economics, computer science, engineering, or other related business or quantitative discipline preferred. Relevant experience considered in lieu of a degree. 

• Active DoD Secret clearance required. Must have at a minimum, an Interim Secret Clearance. 

• 10 years of experience with Python, and strong experience with PySpark or similar big data libraries. 

• Knowledge of Army Vantage and data environment standardization. 

• Experience working with data analysis tools including object-oriented programming (Python, Java, SQL, TypeScript), computational analysis tools (R, MATLAB), and associated data science libraries (scikit-learn). 

• Experience developing and implementing statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics as well as to develop statistical tests to make data-driven recommendations and decisions 

• Experience creating m