AI - savvy Data Analyst generating value - driven insights from manufacturing and operational data in hardware manufacturing. Support NPI and automate workflows with statistical analysis, dashboards and AI.
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Senior Internal Auditor – Data Analytics
Posted last month
About the role
- Senior Internal Auditor focused on data pipelines and analytics at Kraken. Building automated tests and monitoring tools within a remote-first crypto exchange setting.
Responsibilities
- Design and build data pipelines that connect to source systems, transform raw data into audit-ready datasets, and enable full-population testing across entities and jurisdictions.
- Develop automated test scripts, anomaly detection models, and risk scoring mechanisms that replace manual sampling with continuous, data-driven assurance.
- Validate the completeness and accuracy of data used in analytics — you don’t just visualize data, you first prove it matches the source system.
- Leverage AI-assisted tools to enhance analytics workflows, from accelerating data extraction and transformation to building smarter detection models.
- Partner with SOX testers and operational auditors to translate audit objectives into scalable analytical tests.
- Identify opportunities to leverage emerging technologies, including AI-assisted tools, to enhance coverage and efficiency.
- Build and maintain dashboards and visualizations that provide Internal Audit and senior leadership with real-time insights into control effectiveness, exception trends, testing coverage, and audit findings.
- Design continuous monitoring solutions that shift Internal Audit from periodic, point-in-time testing to ongoing surveillance of control health across critical processes.
- Work with Engineering, Data, and Business Operations teams to identify data sources, understand data lineage, and secure timely access to the data needed for audit analytics.
- Champion a data-first mindset within Internal Audit. Train auditors on analytics tools, build self-service datasets and documentation, and empower non-technical team members to explore data independently.
- Communicate complex data analytical findings clearly to both technical and non-technical audiences, translating data into actionable audit conclusions for senior leadership and the Audit Committee.
Requirements
- 8+ years of experience in data analytics, data science, analytics engineering, or data engineering, with proven application in an audit, risk, or financial services context.
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Information Systems, or a related quantitative field.
- Advanced proficiency in SQL and Python. Experience building data visualizations and dashboards using tools such as Tableau, Power BI, or equivalent.
- Rigorous approach to data quality, including completeness, accuracy, and reconciliation to source systems is second nature, not an afterthought.
- Comfortable integrating AI-assisted tools into analytics workflows. You don't need to be an AI engineer, but you should know how to use AI to work faster and smarter.
- Demonstrated ability to translate ambiguous audit or business questions into structured analytical approaches and scalable solutions.
- Effective communicator who can present complex data findings as clear, actionable conclusions for auditors, senior leadership, and external stakeholders.
Benefits
- Kraken Culture
- Remote work options
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