Integra FEC (Financial Economic Consulting) is a litigation and economic consulting firm that exists to restore integrity to the financial system through forensic data analytics. We work with government agencies and law firms in their efforts to combat a wide array of financial fraud, in areas ranging from securities to healthcare to crypto assets. We are looking for strong candidates with quantitative and financial backgrounds and a natural curiosity to learn to join our team and help tackle complex projects by efficiently analyzing data.
Main responsibilities include:
- Plan, develop, and take ownership in data-intensive investigations related to financial fraud
- Write scripts to retrieve and organize data; parse free-form text fields, images, and spreadsheets to derive insights
- Construct and analyze large datasets to find fraudulent patterns; develop quantitative and empirical methods to analyze potentially fraudulent conduct
- Summarize and present findings to technical and non-technical audiences, through long-form reports, charts and slides
- Anticipated to grow toward managing projects and communicating with clients
Job Qualifications
Required
- 3+ years of relevant work experience
- Background in statistics, mathematics, engineering, computer science, data science, accounting, finance, economics, or other quantitative field
- Demonstrated experience with R, Python, and/or SQL
- Attention to detail
- Intellectual curiosity and interest in fraud analysis
- Highest ethical standards
- Strong teamwork abilities
Preferred
- Excellent skills in R, Python, and/or SQL
- Background in economic/management consulting or finance
- Knowledge of financial concepts and principles
- Knowledge of crypto, decentralized finance, or smart contracts
- Demonstrated aptitude for research
Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
Integra FEC Austin, Texas, USA Office
1801 Lavaca St, Austin, Texas, United States, 78701
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