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Data Analytics Senior Analyst position in Citi Internal Audit Research Labs team, working across Internal Audit to identify innovation and improvement opportunities, and prototype solutions to promote automation, efficiency, and impact. The role involves providing independent assessments of Citi's control environment, risk management and governance for key stakeholders.
Job Responsibility:
Gather and translate business requirements and design end-to-end technical solutions to solve varied problem statements
Understand the applicability of data and analytics in an audit context and be able to use provided self-serve solutions
Applies in-depth disciplinary knowledge, contributing to the development of new techniques and the improvement of processes and workflows
Understand the end-to-end solution design process, including how your work fits into the bigger picture
Understand the end-to-end innovation process (ideation, prototyping, evaluation) and be able to execute elements of the process
Understand the typical solution development lifecycle (plan, design, build, test, adopt) and be able to execute elements of the process
Drive efficiency through implementation of business process and data automation
Continuously identify ways to improve IA processes by exploring and evaluating new data sources, tools, and capabilities
Develop professional relationships with audit teams to assist in the definition of analytics and automation opportunities
Requirements:
Previous relevant experience within Data Analytics
Ability to effectively use complex analytical, interpretive, and problem-solving techniques
Strong interpersonal and multicultural skills for interfacing with all levels of internal and external teams and management
Self-driven, adaptable, curious about learning and developing new skillsets
Excellent analytical and problem-solving ability, able to understand business processes and develop appropriate solutions
Detail oriented approach, consistently performing diligent self-reviews of work product, and attention to data completeness and accuracy
Strong verbal and written communication skills with ability to explain technical subjects to non-technical stakeholders
Proficiency in one or more of the following technical skillsets: data manipulation, scripting, and automation (including experience with libraries such as Pandas and NumPy)
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