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Ernst & Young - Kansas City, MO
posted 2 months ago
About the position
The Senior Risk Consulting position in Digital Risk at EY focuses on helping clients develop, implement, and enhance their technology risk and compliance programs. This role involves leading teams to address complex data-related challenges, ensuring compliance with regulations, and integrating advanced technologies to manage risks effectively. The position requires a blend of technical expertise in data analytics and risk management, along with strong client engagement skills.
Responsibilities
- Operate as a team leader for engagements to help clients develop and strengthen their IT risk and compliance programs.
- Review clients' IT processes and controls, remediate and implement controls, and onboard new tools into risk and compliance frameworks.
- Assist with readiness and adherence for new compliance regulations.
- Design and implement solutions to data-related technical/compliance challenges such as DevSecOps and data governance.
- Leverage data analytics tools/software to build scalable solutions through data analysis and visualizations using SQL and Python.
- Collect, clean, and interpret large datasets from multiple sources, ensuring data integrity.
- Integrate next-generation technologies such as cloud platforms and machine learning.
- Develop custom scripts and algorithms to automate data processing and analysis.
- Analyze data to uncover trends and generate insights for business decisions.
- Build and maintain relationships across various teams to drive effective financial risk management.
- Work with DevSecOps and Security Assurance teams to improve control environments and implement automation.
- Bridge gaps between IT controls and business controls, ensuring a complete control environment is managed.
Requirements
- Experience in data architecture, data management, data engineering, data science, or data analytics.
- Experience in building analytical queries and dashboards using SQL, noSQL, Python, etc.
- Proficient in SQL and quantitative analysis, capable of drawing meaningful insights from large datasets.
- Knowledge of scripting and programming tools such as Python, SQL, R, Java, and Scala.
- Familiarity with Big Data tools like Hadoop, Hive, and Pig.
- Experience with data management tools such as Informatica and Oracle.
- Knowledge of predictive analytics tools like Python and SAS.
- Experience with data visualization tools such as Tableau and PowerBI.
- Ability to analyze complex processes to identify potential risks across finance cycles.
- Experience with DevSecOps practices and security integration in product development.
Nice-to-haves
- Experience in managing technical data projects.
- Experience in developing statistical model tools and techniques.
- Experience in implementing data quality processes.
- Experience in developing data services in a cloud environment.
- Experience in process management and optimization.
Benefits
- Comprehensive compensation package
- Performance-based rewards
- Recognition for value brought to the business
