Security Summit Data Analyst 026P-0117
The Security Summit Data Analyst supports government-led fraud analytics efforts under the Security Summit Analytics task area, focusing on protecting taxpayer data and strengthening identity theft detection and prevention programs. This role is responsible for analyzing complex datasets, supporting partner reporting, and ensuring high data quality across collaborative initiatives involving federal agencies, states, and private sector partners.
The ideal candidate is a detail-oriented and analytically rigorous professional who can translate data into actionable insights while operating in a fast-paced, mission-critical environment. This individual is expected to work independently with minimal supervision, proactively identify data anomalies and trends, and support continuous improvement of fraud detection capabilities.
This role directly contributes to identifying fraud patterns, improving reporting accuracy, and enhancing coordination across stakeholders. The analyst will leverage tools such as SQL, Python, Power BI, and data quality frameworks to ensure reliable and timely insights that inform operational and strategic decisions.
Key Responsibilities / Day-to-Day Activities
- Analyze large, complex datasets to identify fraud patterns, anomalies, and emerging risks
- Develop and maintain reports and dashboards to support Security Summit partner reporting requirements
- Perform data validation, cleansing, and reconciliation to ensure accuracy and integrity of analytical outputs
- Collaborate with internal and external stakeholders to gather requirements and translate them into analytical products
- Monitor key performance indicators and operational metrics related to fraud detection and prevention
- Support development and refinement of business rules, filters, and analytical measures
- Conduct trend analysis across filing and non-filing periods to identify shifts in fraud behavior
- Prepare briefings, summaries, and visualizations to communicate findings to technical and non-technical audiences
- Assist in integrating and evaluating internal and external data sources to enhance analytical capabilities
- Document methodologies, assumptions, and data lineage to support transparency and reproducibility
How to Apply
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| Job Category | Data Analysis and Analytics |
| MINIMUM QUALIFICATIONS | Bachelor’s degree in Data Analytics, Statistics, Computer Science, Economics, or a related field | 4 to 6 years of experience in data analysis, reporting, or business intelligence |
| REQUIRED SKILLS | Proficiency in SQL for data extraction, transformation, and analysis | Experience with data visualization tools such as Power BI, Tableau, or similar |
| TECHNICAL SKILLS | Strong analytical and problem-solving skills with attention to detail | Experience with data quality management and validation techniques | Ability to communicate complex analytical findings clearly and effectively | Experience working with structured and unstructured data in large-scale environments |
| DESIRED QUALIFICATIONS | Experience supporting federal programs, particularly IRS, Treasury, or fraud analytics initiatives | Familiarity with identity theft, fraud detection, or financial crimes analytics | Proficiency in Python or R for advanced analytics and data manipulation | Experience working in collaborative, multi-stakeholder environments | Knowledge of predictive modeling concepts, business rules engines, or anomaly detection techniques | Experience with cloud-based data platforms such as AWS or Azure | Relevant certifications such as Certified Analytics Professional (CAP), Microsoft Power BI Certification, or similar |
| SUITABILITY REQUIREMENTS | Ability to obtain and maintain a Public Trust clearance |