SENIOR DATA ANALYST

The Sr. Data Analytics Analyst will be a key Subject Matter Expert and contributor in the Internal Audit Services (IAS) continued enhancement of data analytics, data mining, and continuous auditing strategies and tactics in support of the audit charter.  He or she completes all internal audit work in compliance with established audit methodology while meeting all organizational and professional ethical standards.

Key responsibilities include:

Performance of Analytics (70%)

· Ability to access and analyze complex data; use of analytical tools and languages such as Alteryx and Python; and ability to interpret, visualize and communicate results using dashboarding tools such as Tableau and Power BI.

· Provide both advisory and execution support in audits by identifying, developing, documenting, or executing audit analytics during all relevant stages of an audit.

· Perform data mining and analysis to facilitate the identification and communication of outliers and trends in the business.

· Perform descriptive, statistical, and text analytics to test if the business is meeting its operational, financial, and regulatory requirements and benchmarks. 

· Design and execute standalone Data Analytics audit projects as warranted in support of department objectives.

· Assist auditors in obtaining necessary data for audits.  Identify, develop, and maintain continuous auditing/monitoring activities.

· Provide additional support on audits or other IAS initiatives when necessary.

Business Knowledge, Technical Knowledge, and Individual Development (20%)

· Actively learn and apply mature and emerging technical knowledge gained through professional development opportunities, including external and internal training.

· Actively seek to build and apply business knowledge to complement technical expertise in design and performance of analytical procedures.

Department Development (10%)

· Assist in, and sometimes lead, department initiatives to review and improve department processes, tools and methodologies related to the use of Data Analytics.

· Mentor colleagues and provide training on professional standards, best practices, tools, and strategies for personal and department success.