Audit Data Strategist – Experienced Manager

Location:

Atlanta, Baltimore, Boston, Chicago, New York

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

Data has yet to be utilized to its fullest potential. Clients are looking to build smarter and more efficient ways to operate through new opportunities uncovered by their data. Our clients look to us as trusted advisors to provide insights on how to ingest, interpret and manage data. We focus on business intelligence, advanced analytics and information management.

We provide constant room for growth through client engagements and personal development. Our practitioners develop and lead innovative data techniques and methods, supporting both business and technology leaders. This role provides the unique opportunity to build a professional network, tackle complex data issues and drive cutting‑edge approaches. The experiences you gain here will be more valuable than anywhere else.

• Work on large‑scale client projects supporting the Audit Innovation and Digital platform
• Drive high‑quality work products by analyzing complex data through utilization of a suite of analytical tools and delivering a range of analytics results in written and presentation formats.
• Develop repeatable data delivery process enablers for frequently used financial systems.
• Extract data from multiple sources including structured, semi‑structured and unstructured data
• Leverage data to solve strategic, tactical, structured and unstructured business problems through interpreting complex data from multiple sources and translate into actionable insight for the audit teams and clients.
• Manage the delivery of data science insights using a range of tools and methods to create cognitive services involving complex algorithms, machine learning and artificial intelligence methods.
• Create work papers that document the engagement procedures performed in a concise and organized manner.
• Lead diverse teams of professionals across different geographies to efficiently and effectively deliver high quality work products to clients.
• Provide on‑the‑job training to analyst team for data analysis methodology, software tools, project management, and interpersonal skills.
• Establish and manage priorities and work plans, communicate project status to manager, report all chargeable hours and deliver work by agreed upon deadlines.
• Stay informed of analytics solutions, auditing and accounting standards that affect business processes analyzed and apply analytics approach with expected level of assistance and supervision.
• Comply with firm policies and guidelines, AICPA Code of Professional Conduct, and other professional standards.
• Develop and maintain relationships with clients (external and internal) and commit to improving client satisfaction.
• Assist with scoping the nature and extent of projects to be undertaken.
• Confer and communicate with clients to execute engagement plan.

• A bachelor’s degree in Computer Science, Operations Research, Math, Statistics, Economics or Industrial Engineering and approximately three years of related work experience; or a graduate degree in the same and approximately two years of related work experience.
• Practical experience in leading and managing teams through a product life cycle — requirements, design, development and testing
• Practical experience using the following tools and technologies:
• Advanced analytics: SAS, R, Python, SPSS, MapR, Flume, Hue, Impala, predictive analytics, machine learning, artificial intelligence
• Business intelligence and visual analytics: OBIEE, Micro Strategy, Business Objects, Cognos, Spotfire, Qlik, Tableau, and Power BI
• Information Management:
  Informatica, Data Stage, SSIS, Talend, SQL, Alteryx, Hadoop, Hortonworks, Cloudera, Kerberos, Apache Sentry, Knox, Collibra, AWS, legacy vendor software
• Advanced proficiency and experienced in statistical modelling and machine learning techniques
• Proficiency in at least one programming language used in data science
• Excelle…