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Senior Data Scientist – Financial Fraud Analytics (2 Openings)

Vinsys Information Technology Inc

Remote · Contrato

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Experiência
Mais de 10 anos
Salário
Vagas
2
Publicado
há 1 hora
Modo de trabalho
Trabalhe em casa
Educação
Master's or higher in Data Science or related field
Retomar
Obrigatório candidatar-se

Descrição da vaga

Opportunity Overview

Vinsys Information Technology Inc is urgently seeking two Senior Data Scientists to join a federal government project focused on financial fraud detection and criminal investigation analytics for the SBA Office of Inspector General. This role involves remote work with occasional onsite requirements.

Key Responsibilities

  • Design and manage supervised and unsupervised machine learning models including regression, classification, clustering, Bayesian, ensemble, anomaly detection, and predictive analytics.
  • Process and analyze a variety of structured and unstructured large datasets while ensuring data quality and consistency.
  • Create repeatable data integration, cleaning, and analysis workflows.
  • Collaborate extensively with criminal investigators and auditors to detect financial fraud, improper payments, and noncompliance within federal programs.
  • Develop, validate, and maintain indicators for potential loan fraud and program noncompliance.
  • Implement advanced natural language processing techniques such as OCR, semantic similarity, text classification, and deployment of large language models.
  • Conduct data manipulation and analysis primarily using Python (including Pandas) and SQL (SQL Server, PostgreSQL).
  • Produce dashboards, visualizations, reports, executive summaries, and detailed documentation consistent with evidentiary standards for criminal investigations.
  • Present analytical outcomes and recommendations to both technical teams and nontechnical government stakeholders.
  • Work closely with data engineers to ensure cloud architectures (e.g., Azure) effectively support analytics and machine learning workflows.
  • Automate data processes using Python, Microsoft Excel, Power BI, Power Apps, SharePoint, and related technologies.
  • Uphold strict confidentiality of sensitive government and personal information.

Required Qualifications

  • Master's, Ph.D., or equivalent level degree in Data Science, Machine Learning, Computer Science, Mathematics, Statistics, or similar fields; or at least 10 years of professional experience.
  • Minimum 5 years of hands-on experience designing and implementing AI systems and predictive modeling.
  • At least 5 years developing supervised and unsupervised machine-learning algorithms.
  • Experience of 5 years or more in developing regression, classification, anomaly-detection, and predictive models.
  • 3 or more years supporting criminal investigations related to financial fraud or government fund misuse.
  • Strong Python skills with at least 3 years of data manipulation expertise, especially using Pandas.
  • Experience with cloud platforms (Azure, AWS, or GCP) for 3 or more years.
  • Advanced SQL proficiency (minimum 2 years) including SQL Server and PostgreSQL.
  • At least 2 years of experience developing and deploying NLP solutions.
  • Proven ability to communicate complex technical analyses effectively to diverse audiences.
  • Excellent writing, speaking, and documentation skills.
  • Eligibility to pass a federal public-trust background investigation and possession of a valid Social Security number.

Preferred Qualifications

  • Certifications in Azure, AWS, Google Cloud, data science, or machine learning domains.
  • Previous experience with federal law enforcement or Inspector General agencies.
  • Familiarity with SBA loan programs, financial fraud detection, government benefit programs, or improper payments.
  • Skills in deriving investigative leads from the results of analytical models.
  • Experience with Power BI, Power Apps, SharePoint, OCR technology, semantic search tools, and large language models.
  • Understanding of federal regulations on criminal-investigative information, including Federal Rule of Criminal Procedure 6(e).

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