Senior Data Scientist

Location: Remote

Duration: 1+ Year

Federal Requirement

Mandatory Education and Experience
Consultants must meet one of the following education or overall experience requirements:
Master's, Ph.D., doctorate, or equivalent advanced degree in data science, machine learning, computer science, mathematics, statistics, or a related discipline; or
At least ten years of applied professional experience in one or more of these fields.

Five or More Years of Hands-On Experience in Each Area
Designing, implementing, and maintaining advanced AI systems and predictive models.
Developing both supervised and unsupervised machine-learning models.
Developing analytical rules and models using current analytical tools and industry best practices.
Developing regression, classification, statistical, anomaly-detection, or predictive models.

Three or More Years of Hands-On Experience in Each Area
Providing analytical or data support for criminal investigations involving financial fraud, misuse of government funds, improper payments, or comparable misconduct.
Manipulating, cleansing, transforming, and analyzing data using Python.
Using the Python Pandas library.
Working in a modern cloud environment such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform.

Two or More Years of Hands-On Experience in Each Area
Conducting advanced data analysis using SQL.
Working with both SQL Server and PostgreSQL.
Developing and scaling natural-language-processing solutions.
Presenting analytical methodologies and findings to technical and nontechnical stakeholders.
Preparing written reports, dashboards, data visualizations, or executive-level analytical products.

Preferred Qualifications
Microsoft Azure, AWS, Google Cloud, data science, machine learning, or AI certification.
Experience with Azure Machine Learning and Azure Synapse Analytics.
Experience supporting federal law-enforcement agencies, Inspectors General, auditors, or criminal investigators.
Experience developing investigative leads involving loan fraud, financial fraud, grant fraud, improper payments, or abuse of public funds.
Experience integrating approved large-language models with enterprise datasets.
Experience with explainable AI, responsible AI, model validation, model monitoring, and model-risk documentation.
Experience creating Power BI dashboards, network graphs, geographic maps, and investigative visualizations.
Knowledge of evidentiary documentation and chain-of-custody considerations.
Experience working with protected or sensitive investigative data.

Technical Skills
Python and Pandas
SQL Server and PostgreSQL
Supervised and unsupervised machine learning
Regression and classification
Clustering and anomaly detection
Bayesian and ensemble methods
Natural-language processing
OCR and semantic-similarity methods
Large-language-model integration
Azure Machine Learning
Azure Synapse Analytics
Power BI
Microsoft Excel
Power Apps
SharePoint
Data visualization and dashboard development
Git or comparable source-control tools