Senior Data Analyst

To support Internal Audit’s data-driven audit testing strategy and the development of Continuous Risk Assessment (CRA). Perform complex analytical and statistical modeling on large data sets to provide Internal Audit leadership, risk partners, and business unit Management with actionable intelligence and insights on key risks to business processes and controls. Define data requirements, perform data collection, processing, cleaning, analysis, modeling and visualization on systems and data from all lines of business. Design, automate and publish data pipelines and dashboards that provide continuous monitoring capabilities. Lead complex data analysis projects with minimal supervision and wide latitude for independent judgment. Consult with audit teams and other stakeholders to advise on data analytics best-practices on audit engagements. Effectively manage projects from inception through deployment and maintenance.

 

• Develop, maintain, and manage advanced reporting, dashboards, data models and analytical results
• Evaluate and define functional requirements for analytics and business intelligence (BI) solutions
• Retrieve, analyze and validate data and test accuracy of reported results
• Work directly with project leads to understand requirements and propose key analytics solutions to drive effective decision-making and influence business objectives
• Produce actionable reports that demonstrate key performance indicators, identify areas of improvement for current operations, and show root cause analysis of problems
• Analyze and summarize business operations, customer and/or economic data in order to improve business intelligence, optimize operating effectiveness and predict business outcomes
• Identify trends and patterns in business data; create data visualizations to support business decision making
• Build new and/or modify existing database/data warehouse/data mart and business intelligence solutions to meet business and system requirements
• Collaborate with business units and senior management to conduct needs assessment to support business unit objectives
• Support complex Data Science and Big Data projects
• Effectively communicate data outcomes to business stakeholders and leadership
• Mentor and guide less experienced staff
  
   

• Bachelor’s degree in Business, Finance, Statistics, Information Systems, Computer Science, Data Science, Data Analytics, or a related field, or the equivalent combination of training, education and experience
• Significant hands-on experience in the use of business intelligence tools such as PowerBI, Tableau, Cognos, Qlick, or similar)
• Significant hands-on experience in the application of statistical methods, mathematical techniques, forecasting, cost-benefit analysis, related analytical tools and programming languages (Python, R, SAS or similar)
• Advanced hands-on SQL skills for extraction, transformation and analysis of data
• Advanced skill analyzing statistics and reports to determine business performance and trends
• Advanced skill interpreting, extrapolating and interpolating data for statistical research and modeling 
• Significant experience that demonstrates the ability to research, compile, and document data, business processes, and workflow
• Advanced skill identifying and analyzing business requirements and recommending solutions
• Effective skill presenting findings, conclusions, alternatives and information clearly and concisely
• Working knowledge of standard ETL tools and techniques
• Working knowledge of the process in sourcing raw data and cleansing techniques
• Working knowledge of data warehousing, data cleaning, and other analytical techniques required for data usage
• Advanced skill in understanding and communicating data presented in models, charts, and tables and transforming it into a format that is useful to the business and aids effective decision making
• Advanced skill in the use of measurement and statistical practices to analyze current and historical data to make predictions, identify risks, and opportunities enabling better decisions on planned/future events
• Advanced skill in understanding and analyzing models that predict the probability of an outcome
• Advanced knowledge of and the ability to perform basic statistical analysis such as measures of central tendency, normal distribution, variance, standard deviation, basic tests, correlation, and regression techniques
• Significant experience in problem resolution including determining root cause, scope and scale of issues
• Advanced skill in collecting and manipulating data used in effective decision making
• Working knowledge of data models, design tools and business/technical requirements
• Demonstrates a key understanding of mu