Principal II - Fraud Analytics Lead (Consulting Manager)

Guidehouse Inc.; Arlington (VA); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Onsite work in Lanham, MD

Job summary

Guidehouse Inc. is seeking a Principal II Fraud Analytics Lead to provide strategic technical leadership for fraud analytics operations, methodologies, and platform integration.

The role involves guiding cross-workstream direction, developing analytics strategies, and advising on complex fraud detection challenges. Responsibilities include defining detection methodologies, leading analytics teams, and presenting findings to executives.

Qualifications

• Bachelor’s degree in a STEM field or equivalent.
• Eight or more years of professional experience in fraud analytics, cybersecurity analytics, or related technical delivery.
• Experience leading analytical workstreams across multiple teams.

Responsibilities

• Provide strategic technical leadership for fraud analytics operations and platforms.
• Develop and apply analyses to identify fraudulent activity and emerging risks.
• Lead delivery of complex analytical products and recommendations.
• Define fraud indicators, detection methodologies, and predictive models.
• Collaborate with stakeholders to integrate data mining results with systems and improve analytics performance.
• Prepare technical briefings, dashboards, and executive summaries.

Skills

Fraud analytics

Leadership

Python

SQL

Machine learning

Data visualization

Education

Bachelor’s degree in Data Science/CS/Statistics/Math

Tools

Splunk

Elasticsearch

Spark

Parquet

SIEM (Splunk)

Job description

Job Family : Data Science & Analysis

Travel Required : None

Clearance Required : Ability to Obtain Public Trust

What You Will Do :

• The Principal II Fraud Analytics Lead will provide strategic technical leadership for fraud analytics operations, analytical methodologies, platform integration activities, and investigative initiatives. This position establishes analytical approaches, guides technical direction across workstreams, and advises stakeholders on complex fraud detection and analytic challenges.
• Establish analytical strategies, methodologies, and priorities supporting fraud analytics, predictive analytics, forensic analysis, data mining, and cybersecurity monitoring initiatives.
• Develop and apply in-depth analyses of complex data to identify fraudulent activity, anomalous behavior, root causes, emerging risks, and potential attack vectors.
• Exercise independent judgment in selecting analytical methods, techniques, tools, and evaluation criteria to obtain results and inform decision-making.
• Provide technical leadership, mentorship, and strategic direction across analytical workstreams while reviewing and approving complex analytical products and recommendations.
• Define, refine, and oversee implementation of fraud indicators, detection methodologies, predictive models, analytical frameworks, and statistical analysis approaches.
• Collaborate with stakeholders to integrate data mining results with existing systems, improve analytics performance, and recommend process or technology enhancements.
• Prepare and present technical briefings, reports, executive summaries, dashboards, and recommendations based on analytical findings and operational priorities.
• Support data ingestion, schema alignment, data quality review, extract, transform, load activities, and analytics workflow improvements.
• Identify alternative applications for existing tools, techniques, and technologies to improve fraud analytics outcomes and operational effectiveness.
• Advise government and contractor leadership on fraud trends, emerging risks, analytical priorities, and opportunities to improve fraud detection effectiveness.
• Work onsite at the client location in Lanham, Maryland five (5) days per week and collaborate closely with government personnel and contractor team members.

What You Will Need :

• Ability to obtain and maintain a Public Trust clearance.
• Bachelor's degree in Data Science , Computer Science, Cybersecurity, Information Systems, Statistics, Mathematics, Engineering, Operations Research, Information Science, or a STEM related field.
• EIGHT (8) or more years of professional experience supporting fraud analytics, cybersecurity analytics, data science, data engineering, predictive analytics, incident response, investigations, platform advisory, or related technical delivery.
• Experience leading analytical workstreams, technical tasks, or program segments in data analytics, fraud analytics, cybersecurity, systems integration, or platform advisory environments.
• Experience establishing analytical strategies, technical approaches, or fraud detection methodologies across multiple teams or workstreams.
• Experience developing and applying in-depth analysis of complex data using professional concepts, methodologies, and independent judgment.
• Experience with machine learning, statistical modeling, predictive analytics, data mining, link analysis, network analytics, text mining, data visualization, or related analytical techniques.
• Experience preparing and presenting technical reports, briefings, dashboards, recommendations, or executive-ready analytical products.
• Experience providing technical leadership, direction, or mentorship to team members completing analytics, data integration, documentation, or investigative tasks.
• Experience using tools and technologies such as Python, R, Java, Linux shell scripting, SQL/no-SQL databases, Spark, Elasticsearch, Parquet, SIEM platforms including Splunk, Microsoft Word, Microsoft Excel, and Microsoft PowerPoint.
• Experience with web development languages and frameworks such as HTML, Python/Flask, JavaScript, CSS, jQuery, or React in support of platform advisory, analytics ecosystem, data/application integration, dashboard, or application-facing analytics work.
• Ability and willingness to work onsite at the client location in Lanham, Maryland five (5) days per week.

What Would Be Nice To Have :

• Experience leading fraud analytics, cybersecurity analytics, data science, or incident response teams in a federal or large enterprise environment.
• Experience supporting online application monitoring, identity verification, digital identity, credential service provider integrations, or large-scale transaction monitoring environments.
• Experience developing or guiding machine learning models, predictive models, statistical models, analytical algorithms, fraud indicators, or detection logic.
• Experience with SIEM platforms, including Splunk, cybersecurity monitoring technologies, or large-sc