The FamilySearch Fraud Prevention Intern will work with data and analytics to improve the fraud prevention process.
Church employees find joy and satisfaction in using their unique talents and abilities to further the Lord's work. From the IT professional who develops an app that sends the gospel message worldwide, to the facilities manager who maintains our buildings- giving Church members places to worship, teach, learn, and receive sacred ordinances-our employees seek innovative ways to share the gospel of Jesus Christ with the world. They are literally working in His kingdom.
Only members of the Church who are worthy of a temple recommend qualify for employment. Apart from this, the Church is an equal opportunity employer and does not discriminate in its employment decisions on any basis that would violate U.S. or local law.
Qualified applicants will be considered for employment without regard to race, national origin, color, gender, pregnancy, marital status, age, disability, genetic information, veteran status, or other legally protected categories that apply to the Church. The Church will make reasonable accommodations for qualified individuals with known disabilities.
- Strong analytical and problem-solving skills with the ability to interpret complex datasets and identify meaningful trends, anomalies, or suspicious behaviors.
- Proficiency or coursework experience in programming languages such as Python, SQL, R, or similar analytical tools.
- Familiarity with exploratory data analysis (EDA), statistical analysis, and data visualization techniques.
Paid Interns are qualified while enrolled in an educational institution and for one year following graduation. They must sign a Paid Internship Engagement Letter.
- Assist in managing Action Plans by preparing reports, conducting exploratory data analysis (EDA), tracking progress, and documenting findings.
- Support fraud analytics initiatives by identifying unusual patterns, behaviors, and anomalies in complex datasets.
- Help develop and test statistical and machine learning methods for fraud and anomaly detection, and contribute ideas for improving existing approaches.
- Perform data cleaning, transformation, validation, and quality assurance activities on large datasets.
- Assist with ETL (Extract, Transform, Load) processes and help support data pipelines and analytical workflows.
- Develop dashboards, summaries, visualizations, and recurring reports for management and operational teams.
- Acquire and organize data from multiple primary and secondary data sources while maintaining data integrity.
- Conduct behavior analysis and trend analysis to support investigations and operational decision-making.
- Support field investigation follow-up by organizing, reviewing, and summarizing findings from investigative documentation.
- Collaborate with team members to prioritize analytical tasks, contribute process improvement ideas, and support ongoing projects.
- Document analytical methods, findings, and recommendations for both technical and non-technical audiences.
- Participate in research and development of new fraud prevention and process improvement opportunities.