20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You spend time finding and reviewing documents in Microsoft SharePoint and emails in Outlook, then pulling data from Microsoft Excel or SQL Server. Mornings often start with checking new incidents or subpoenas and triaging what needs urgent review.
Afternoons often mean writing reports in Word or slides in PowerPoint, tracing transactions with SQL queries or Python scripts, and meeting managers or legal to recommend next steps.
Expect heavy use of Microsoft SharePoint for document storage, Outlook for communications, Excel for data review, Word for reports, and PowerPoint for presentations.
For technical work you’ll use Microsoft SQL Server to query logs, Python for data parsing or automation, and tools like Splunk Enterprise to search system and security logs.
Yes — use AI to summarize documents, draft interview questions, or extract entities from emails. But never feed sensitive personal data or unredacted financial records into public AI services.
Keep AI inside approved systems or on-premise models, log what you run, and verify AI outputs by checking the original source in SharePoint, SQL queries, or raw Splunk logs before acting.
According to the U.S. Bureau of Labor Statistics (BLS), there are about 132,130 people employed in this occupation with a median salary of $81,100 per year.
The lowest tenth earn about $48,460, and the top tenth earn about $151,490 per year, per BLS data.
A Fraud Investigator focuses on proving crimes: gathering evidence, interviewing witnesses, and arresting or recommending charges. They often work closely with law enforcement.
A Data Privacy Analyst concentrates on protecting personal data, running audits, interpreting privacy law, liaising with regulators, producing reports, and using systems like SharePoint, SQL Server, and Splunk to trace and document data handling.
SQL querying in Microsoft SQL Server. You’ll use SELECT queries to trace transactions, join tables to find related records, and pull datasets to feed Excel, Python, or Splunk searches.
If you can write basic SQL and export clean CSVs, you’ll already speed up audits, reports, and investigations.