Description:
The Senior Data Scientists will design, develop, test, calibrate, and maintain advanced statistical, artificial intelligence, machine-learning, and natural-language-processing solutions. The selected candidates will work closely with criminal investigators, auditors, data engineers, and government stakeholders to identify potential financial fraud, improper payments, and noncompliance within federal programs.
Key Responsibilities
- Design, implement, and maintain supervised and unsupervised machine-learning models.
- Develop regression, classification, clustering, Bayesian, ensemble, anomaly-detection, and predictive models.
- Analyze large relational, structured, semi-structured, and unstructured datasets.
- Conduct data-quality assessments and identify inconsistencies, abnormalities, and incomplete records.
- Develop repeatable processes for combining, cleaning, and analyzing large datasets.
- Support criminal investigations involving financial fraud, improper payments, and misuse of government funds.
- Collaborate with investigators to develop analytical strategies and investigative leads.
- Develop, test, and maintain indicators of potential loan fraud and noncompliance.
- Implement natural-language-processing solutions using OCR, semantic similarity, text classification, and large language models.
- Manipulate and analyze data using Python, including Pandas.
- Conduct advanced analysis using SQL Server and PostgreSQL.
- Develop dashboards, visualizations, executive summaries, investigative reports, and technical documentation.
- Present analytical methods, findings, risks, and recommendations to technical and nontechnical stakeholders.
- Maintain methodology, model, and analytical documentation consistent with criminal evidentiary requirements.
- Coordinate with data engineers to ensure the Azure architecture supports analytics and machine-learning workloads.
- Develop automation using Python, Microsoft Excel, SharePoint, Power BI, Power Apps, and related tools.
- Protect sensitive government, investigative, and personally identifiable information.
Required Qualifications
- Master's degree, Ph.D., or equivalent doctorate-level degree in Data Science, Machine Learning, Computer Science, Mathematics, Statistics, or a related discipline; or
- At least 10 years of applied professional experience in one or more of these fields.