Part-time Data Quality Analyst (Fraud Investigation)

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Written by AI from the job title and company, not by owl.co, so some details may not match this job. The employer's own page has the real description.

Job Overview

As a Part-time Data Quality Analyst specializing in Fraud Investigation at Owl.co, you will play a vital role in ensuring the integrity and reliability of data within our systems. Your primary responsibility will include analyzing data sets to identify anomalies and trends that may indicate fraudulent activities, thus aiding in the prevention and mitigation of potential fraud risks. Collaborating with our fraud investigation team, you will utilize your analytical skills to enhance data quality and support informed decision-making processes.

Job Responsibilities

• Analyze data sets to identify patterns and anomalies correlating with fraudulent behavior.
• Conduct regular data audits to verify accuracy and integrity of data entries.
• Collaborate with fraud investigation teams to support ongoing investigations with relevant data insights.
• Document findings and prepare reports summarizing analysis results to facilitate decision-making.
• Develop and maintain data quality metrics and dashboards for ongoing evaluation.
• Propose and implement data quality improvement processes and best practices.

Qualifications

• Bachelor's degree in Data Analytics, Computer Science, or a related field.
• Proven experience in data analysis, preferably within a fraud investigation context.
• Strong proficiency in data analysis tools such as SQL, Excel, and data visualization software.
• Excellent analytical and problem-solving skills with a meticulous attention to detail.
• Ability to communicate complex data findings clearly to non-technical stakeholders.
• Experience in working with large and complex data sets.

Technologies & Tools

The Part-time Data Quality Analyst will primarily utilize technologies and software such as SQL for database management, Microsoft Excel for data manipulation, and various data visualization tools such as Tableau or Power BI to present analysis results effectively. Familiarity with data programming languages such as Python or R may also be beneficial in enhancing analytical capabilities.

Ideal Candidates

The ideal candidate for this position will possess a proactive attitude and a strong commitment to data integrity and quality. They should exhibit exceptional analytical thinking and a passion for uncovering insights through data. A candidate who is adaptable and able to thrive in a dynamic environment will excel in this role. Strong interpersonal skills to collaborate effectively with team members and stakeholders while maintaining a high degree of professionalism are also key attributes for success.