Data Scientist; Vantage - Clearance Required
LMI Government Consulting
About the role
Position: Data Scientist (Vantage) - Clearance Required Location: Mt Rainier
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: Hybrid; at least 3 days on client site in Crystal City VA or Aberdeen MD. Open to Remote Responsibilities • Data Engineering: Extract, transform, and load data using big data platforms such as 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 to make it 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 domains, gathering customer requirements and delivering comprehensive statistical analysis to answer questions. • 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. • Created 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 • Bachelor's degree in data science, mathematics, statistics, economics, computer science, engineering, or related 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 OOP (Python, Java, SQL, Type Script), 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 and to develop statistical tests to make data‑driven recommendations. • Experience creating meaningful data visualizations and interactive dashboards using platforms such as Tableau, Qlik, Power BI, RShiny, Plotly, or D3.js to communicate findings and relate them back to how insights create business impact. • Experience with data modeling, building “objects” (e.g., “Soldier,” “Tank,” “Unit”) and defining how they relate to one another in the Foundry environment. • Strong background in Dev Ops and Software Engineering, including Git Lab CI/CD, Infrastructure as Code, and implementing QA practices like Test‑Driven Development (TDD) and unit testing (Pytest). • Proven ability to design and scale Medallion Lakehouse Architectures, implement Data Mesh concepts, and utilize Dimensional Modeling (Star Schemas) on cloud platforms like Databricks or DoD Advana. • Innovative problem solving and…
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