Fraud Analytics Senior Consultant Lead (Senior Consultant II)

Guidehouse•Arlington, VA

4d•Onsite

About The Position

The Fraud Analytics Senior Consultant Lead will support highly specialized fraud analytics activities across the Cybersecurity Fraud Analytics and Monitoring program. This position will independently assess difficult technical and analytical problems, develop practical alternatives and recommendations, support strategic, tactical, and operational planning, and coordinate task-level activities focused on predictive analytics, deep forensics, fraud detection, incident support, data integration, and continuous enhancement of analytics capabilities. Support highly specialized fraud analytics activities related to predictive analytics, forensic analysis, cybersecurity monitoring, fraud detection, incident support, and continuous enhancement. Coordinate analytical activities across assigned workstreams, review analytical products for quality and consistency, and provide guidance to junior team members supporting fraud analytics initiatives. Assess difficult technical and operational problems across fraud analytics, data ingestion, application monitoring, stakeholder coordination, and incident response environments. Develop practical alternatives, recommendations, and solution options that consider client requirements, operational priorities, data limitations, and cybersecurity fraud risks. Contribute to strategic, tactical, and operational-level planning for analytics initiatives, application onboarding, data source integration, and fraud detection capability expansion. Support development, refinement, testing, documentation, and implementation of fraud indicators, analytical algorithms, detection logic, predictive models, and forensic analysis approaches. Analyze structured and unstructured data, transaction logs, user behavior, system activity, and investigative information to identify anomalous, malicious, or fraudulent activity. Support root-cause analysis, incident coordination, mitigation recommendations, and timely reporting for suspicious activity, fraud incidents, and emerging threat patterns. Collaborate with application owners, identity management stakeholders, business representatives, and technical resources to understand user behavior, transaction data, data quality, and integration requirements. Support data extraction, transformation, loading, schema alignment, data quality assessment, data source onboarding, and analytics workflow improvements across large-scale environments. Prepare and present technical reports, executive summaries, dashboards, briefings, recommendations, and documentation that communicate findings to technical and non-technical stakeholders. Provide task-level coordination, analytical guidance, and knowledge sharing to support analysts, engineers, data scientists, and operational staff assigned to fraud analytics activities. Work independently on routine activities, receive general direction on new assignments, and ensure work products meet client requirements, quality expectations, and delivery timelines. Work onsite at the client location in Lanham, Maryland five (5) days per week and collaborate closely with government personnel and contractor team members.

Requirements

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 related field; Master's degree preferred.
Five (5) or more years of professional experience supporting fraud analytics, cybersecurity analytics, data science, data engineering, predictive analytics, forensic analysis, investigations, fraud operations, platform advisory, or related technical delivery.
Experience independently solving difficult technical or analytical problems using professional concepts, procedures, and practical judgment.
Experience developing system requirements or supporting strategic, tactical, or operational-level planning for analytics, cybersecurity, fraud detection, or data-driven programs.
Experience analyzing large structured and unstructured datasets, transaction logs, application activity, user behavior, or system data to identify anomalies, patterns, correlations, risks, or potential fraudulent activity.
Experience supporting predictive analytics, machine learning, statistical analysis, data mining, link analysis, network analytics, text mining, data visualization, or related analytical techniques.
Experience supporting data extraction, transformation, loading, data integration, data quality review, schema alignment, or analytics workflow improvement activities.
Experience preparing and presenting technical reports, dashboards, briefings, executive summaries, documentation, or recommendations for technical and non-technical stakeholders.
Experience coordinating with multidisciplinary teams, client stakeholders, technical resources, and operational personnel to clarify requirements, support delivery, and communicate findings.
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 supporting analytics platforms, data integration efforts, dashboard development, reporting environments, or analytical applications.
Ability and willingness to work onsite at the client location in Lanham, Maryland five (5) days per week.

Nice To Haves

Experience supporting fraud analytics, cybersecurity analytics, data science, or incident response programs in a federal, financial services, intelligence community, or large enterprise environment.
Experience supporting digital identity, authentication services, online application monitoring, or large-scale transaction processing environments.
Experience developing, refining, testing, or validating machine learning models, predictive models, statistical models, analytical algorithms, fraud indicators, or detection logic.
Experience supporting incident response, open-source research, threat intelligence, root-cause analysis, mitigation planning, or stakeholder coordination.
Experience supporting data ingestion, schema alignment, data architecture, data quality improvement, platform advisory services, or analytics ecosystem modernization.
Experience developing dashboards or visualizations using Power BI, Tableau, Spotfire, Microsoft Excel, or similar tools.
Familiarity with cybersecurity programs, federal consulting environments, Agile delivery methodologies, or collaborative development environments.
Candidate currently possesses an active Internal Revenue Service (IRS) Moderate Background Investigation clearance or has held one within the last six (6) months.

Responsibilities

Support highly specialized fraud analytics activities related to predictive analytics, forensic analysis, cybersecurity monitoring, fraud detection, incident support, and continuous enhancement.
Coordinate analytical activities across assigned workstreams, review analytical products for quality and consistency, and provide guidance to junior team members supporting fraud analytics initiatives.
Assess difficult technical and operational problems across fraud analytics, data ingestion, application monitoring, stakeholder coordination, and incident response environments.
Develop practical alternatives, recommendations, and solution options that consider client requirements, operational priorities, data limitations, and cybersecurity fraud risks.
Contribute to strategic, tactical, and operational-level planning for analytics initiatives, application onboarding, data source integration, and fraud detection capability expansion.
Support development, refinement, testing, documentation, and implementation of fraud indicators, analytical algorithms, detection logic, predictive models, and forensic analysis approaches.
Analyze structured and unstructured data, transaction logs, user behavior, system activity, and investigative information to identify anomalous, malicious, or fraudulent activity.
Support root-cause analysis, incident coordination, mitigation recommendations, and timely reporting for suspicious activity, fraud incidents, and emerging threat patterns.
Collaborate with application owners, identity management stakeholders, business representatives, and technical resources to understand user behavior, transaction data, data quality, and integration requirements.
Support data extraction, transformation, loading, schema alignment, data quality assessment, data source onboarding, and analytics workflow improvements across large-scale environments.
Prepare and present technical reports, executive summaries, dashboards, briefings, recommendations, and documentation that communicate findings to technical and non-technical stakeholders.
Provide task-level coordination, analytical guidance, and knowledge sharing to support analysts, engineers, data scientists, and operational staff assigned to fraud analytics activities.
Work independently on routine activities, receive general direction on new assignments, and ensure work products meet client requirements, quality expectations, and delivery timelines.
Work onsite at the client location in Lanham, Maryland five (5) days per week and collaborate closely with government personnel and contractor team members.

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Parental Leave
401(k) Retirement Plan
Group Term Life and Travel Assistance
Voluntary Life and AD&D Insurance
Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts
Transit and Parking Commuter Benefits
Short-Term & Long-Term Disability
Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Care.com annual membership
Employee Assistance Program
Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)
Position may be eligible for a discretionary variable incentive bonus