Data Scientist Subject Matter Expert (SME)

Redhorse Corporation•Washington, DC

21h

About The Position

Redhorse Corporation is seeking an executive-level Data Scientist Subject Matter Expert (SME) to provide high-impact advisory and technical services to the National Security Branch (NSB) and senior executive priority programs. In this role, you will serve as the principal technical authority designing advanced machine learning architectures, novel algorithms, and exploratory data pipelines across high-stakes law enforcement, intelligence, and investigative datasets. You will partner directly with senior government stakeholders to turn massive, disparate data environments into decisive operational advantages, delivering high-level briefings, interactive data visualizations, and robust analytical solutions.

Requirements

10 years of experience as a Data Scientist, Data Engineer, or Developer acting as a technical development lead for collecting, cleaning, and analyzing massive datasets to build predictive models.
10 years of experience in software development and programming across multiple languages, statistical packages, dataset manipulation tools, and Artificial Intelligence/Machine Learning (AI/ML) frameworks.
8 years of experience utilizing data systems to acquire, extract, and structure data for research, exploration, and statistical analysis.
8 years of experience analyzing, interpreting, and discovering patterns in complex datasets using exploratory data analysis techniques.
8 years of experience cleaning, manipulating, munging, and sub-setting large-scale structured and unstructured data.
8 years of experience communicating technical findings, risk assessments, and analytical results to non-technical audiences using summary visualizations and tables.
Demonstrated ability to rapidly learn emerging technologies and operate effectively both independently and in mission-critical team environments.
Active Top Secret/SCI with CI Poly.

Nice To Haves

Bachelor’s or Master’s degree from an accredited college or university in Mathematics, Computer Science, Data Science, Physical Science, or a related quantitative discipline.
8 years of experience applying cutting-edge data mining, machine learning, and predictive analytics techniques to correlate disparate events and multi-source datasets.
Natural Language Processing (NLP) expertise, including large-scale document mining and parsing unstructured textual data into structured databases.
Product-agnostic database and enterprise search administration for large-scale data exploitation.
Advanced statistical modeling, hypothesis testing, and time-series trend analysis capabilities.
Demonstrated adaptability and problem-solving skills in resource-constrained environments with limited access to enterprise cloud infrastructure or commercial-scale compute.
Specialized experience in Geospatial analysis, Computer Vision (CV), or multi-source Sensor Fusion.

Responsibilities

Lead and design machine learning, statistical analysis, and complex data science projects across multiple workstreams.
Collaborate directly with internal and external government stakeholders to diagnose system workflows and implement high-impact modernization strategies.
Architect innovative methodologies to ingest, analyze, and exploit large volumes of law enforcement, intelligence, investigative, and business data.
Develop custom mathematical models, data structures, algorithms, and specialized software code to optimize enterprise search and data discovery.
Utilize programming languages such as Python to build production-ready scripts for automated data collection, cleaning, and processing.
Design, test, and validate data quality frameworks and automated verification pipelines to ensure analytical integrity.
Coordinate across multi-disciplinary engineering and functional teams to deploy predictive models and evaluate operational impact.
Analyze multi-source data outputs and deliver clear, actionable recommendations to senior agency leadership.
Develop intuitive data visualizations, infographics, dashboards, and executive summaries to communicate technical findings to non-technical leaders.