Data Scientist - Internal Audit

• Five to eight years of experience in data analysis or data science or a related field, preferably or a technology company with a focus on crowd-based platforms
• Strong understanding of internal audit processes and methodologies and ability to analyze and cross reference multiple databases and run scripts to validate data points

Technical Skills:

• Python proficiency: Advanced knowledge of Python for data manipulation, analysis, and visualization.
• SQL expertise: Ability to write complex SQL queries to extract and transform data from databases.
• API interaction: Comfortable working with APIs to extract data from third-party software tools and integrate them into the analysis process.
• experience with threat/audit investigation on internal proprietary systems
• Experience with LexisNexis software

Industry Knowledge:

• Crowd-based platforms: Understanding of the unique business models and data structures associated with crowd-based companies.
• Internal audit: Experienced in having managed and executed internal control frameworks and risk assessment methodologies.
• Technology industry: Knowledgeable in the technology landscape and relevant regulations.

Other Skills:

• Problem-solving: Ability to identify and map complex data discrepancies and inconsistencies.
• Communication: Excellent written and verbal communication skills to present findings and recommendations to both technical and non-technical stakeholders.
• Attention to detail: Meticulous approach to data analysis to ensure accuracy and completeness.
• Collaboration: Ability to work effectively with cross-functional teams, including auditors, engineers, delivery and customer operations, human resources and other business stakeholders.

Responsibilities:

• Data extraction and Analysis: Retrieve data from internal databases and third-party software tools, to audit data quality, consistency and compliance with company policies.
• Data reconciliation: Develop and implement processes to compare data sets and identify discrepancies.
• Root cause analysis: Investigate and analyze the root causes of data mismatches, providing actionable insights.
• Reporting: Prepare clear and concise reports summarizing audit findings and recommendations.
• Continuous improvement: Collaborate with teams to enhance data integrity and streamline audit processes.
• Other duties as assigned.

Additional Considerations:

• Experience with specific third-party software tools used by your company can be a significant advantage.
• Certifications in data science or auditing can demonstrate the candidates commitment to professional development