Data Analytics Audit Associate

Develop audit tools, dashboards, and/or build quantitative models to drive sustainable and quantifiable improvements to the audit process. This professional needs to have a strong understanding of business processes, risks, and controls in order to enhance audit deficiencies and effectiveness through the development and delivery of audit data analytics. Client Details One of the oldest and largest international banks in the united states provides a variety of services for financial institutions. Description Plans & organizes his/her own data analytics BAU projects in support of audit testing or issue validations, and delivers timely, high quality results. This role will directly report to the SVP & Internal Audit Data Analytics Team Lead. Profile 1-3 years of work experience, certifications, and/or equivalent focused around developing and utilizing data analytics solutions in a data intensive financial services environment, preferably in an audit, compliance, or risk management area is required. Knowledge of internal control environments and audit methodologies is required Accounting/audit/information system certifications (e.g. CPA, CIA, FRM, CFA) or equivalent is a plus but not required. Programming capabilities in SQL, VBA, and Python is required. Experience using Qlik Sense and Alteryx is required. Experience in the use of data modeling, data mining, and predictive analytics is required. Job Offer Hybrid work schedule Professional development within department and company as a whole Opportunity to work across audit department and counterpart groups Close-knit department with opportunity to voice personal opinions Hands on training from senior leadership MPI does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, or based on an individual's status in any group or class protected by applicable federal, state or local law. MPI encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants.