Controls Testing & Data Analytics Specialist

Job Title: Controls Testing & Data Analytics Specialist

Location: Washington, DC (On-site)

Employment Type: Contract (W2 through ZipStaff - No C2C or 1099)

About the Opportunity

ZipStaff is seeking a Controls Testing and Data Analytics Specialist for a newly established fraud risk management program at a major passenger-rail organization.

You will test and monitor controls against a landscape of financial, operational, and cyber fraud risks, and hand structured findings to the Office of Inspector General. This is a hands-on execution seat - not an audit-manager role and not an IT-controls-only role.

What You’ll Do

• Design, build, and execute data-driven control tests across financial and operational risk.
• Build continuous-monitoring scripts and models in SQL, Python, or Power BI.
• Take hotline intake, review anomalous flags, and compile forensic handoffs for the OIG.
• Work with finance and technology to strengthen ICFR and operational fraud controls.
• Recommend how an unstructured fraud framework should mature.

Do not apply if your background is only IT control testing, AML, check fraud, or cyber fraud.

Required Qualifications

• 5+ years personally executing Internal Control over Financial Reporting (ICFR), operational control testing, or SOX compliance - not only directing others.
• Data analytics used to automate testing and flag fraud indicators: SQL, Python, Power BI, ACL, or IDEA.
• Able to stand up process where none exists.
• Able to influence control owners in writing and in the room.
• Ability to work on-site in Washington, DC.
• Must be legally authorized to work in the United States without sponsorship now or in the future.

Preferred Qualifications

• Federally funded entities, infrastructure, transportation, construction, or other project-heavy environments.
• Hotline intake and OIG or investigative handoff.

Benefits

• Health Insurance.
• Dental Insurance.
• Vision Insurance.
• 401(k) + 401(k) matching.
• Paid time off.
• Referral Program.