Internal Audit Innovation Lab - Data Scientist – VP

Key Skills

Aartificial intelligence, Apache Hive, Data science techniques, Data Visualization, Effective communication skills, Employee life cycle, Java Programming, JIRA, Leadership Skill, Natural Language Processing (NLP), Python Programming, SAS, Scrum Agile Methodology, SQL

Job Description

The Audit Innovation function is looking for a Data Scientist – Lead Analyst to join the Innovation Lab. The Audit Innovation and Analytics function works with members of Internal Audit to identify opportunities to apply Machine Learning (ML), Natural Language Processing (NLP) and Artificial Intelligence (AI) to support the activities of the function, both in the analysis of business data and processes as well as Internal Audit activities. The candidate must be proficient in the development and use of technology and tools to develop the models that support these activities, as well as a functional knowledge of banking processes and related risks and controls.

Key Responsibilities:

• Leadership and subject matter expertise in the development of Data Science projects in support of audit processes improvements.
• Responsible for developing algorithms to solve for complex problems, discovering the organization insights and identifying opportunities through using state-of-the art methods (e.g. statistical, algorithmic, mining and visualization techniques, among others).
• Understanding and support of the Model Risk Management (MRM) process and lifecycle.
• Help shape the direction of machine learning and artificial intelligence.
• Facilitate discussions with the Analytics team about technical challenges; plan and apply scalable solutions.
• Support the creation of leading-edge data products that bring new insights to audit planning and delivery.
• Strong verbal and written communication skills to clearly articulate requirements and results and make practical recommendations for enhancements.
• Detail oriented, performing diligent self-reviews of work product, and attention to data completeness and accuracy
• Develop professional relationships with stakeholders to assist in the definition of audit analytics opportunities.
• Develop effective working relationships with technology and business management of the area being analysed.
• Possesses strong project management and interpersonal skills, makes sound decisions, exhibiting initiative and intuitive thinking
• Requires good analytical skills in order to filter, prioritize and validate potentially complex and dynamic material from multiple sources
• Apply a strong understanding of business processes, risks and controls to identify opportunities to enhance audit efficiencies and effectiveness through the development and delivery of automated processes.
• Promote the use of data science tools and techniques and provide training to team members regarding their use to enhance all phases of the audit process.

Key Qualifications and Competencies

• At least 7 years of practical data science experience, working as a data scientist.
• Work experience in global environment and in large company.
• Excellent technical, programming and databases skills
• Advanced analytic ability and problem solving skills to proactively address business questions with innovative data driven solutions
• Ability to build partnerships with cross-functional teams in order
• Working experience in a quantitative field, Financial/Credit Card industry
• Excellent analytical ability to understand business processes and related risks and controls, and develop innovative audit analytics based upon audit needs.
• Strong interpersonal and multicultural skills for interfacing with all levels of internal and external audit and management.
• Self-driven, problem-solving approach. Understanding of procedures and following these to keep quality and security of processes.

Proficiency in one or more of the following technical skills:

• Python
• SAS
• SQL
• JAVA
• IBM Watson

Proficiency in at least one of the following Data Visualization tools is a plus:

• QlikView
• MicroStrategy

Experience of the following areas would be a plus:

• Natural Language Processing (NLP)
• Business Intelligence including use of statistics, data modelling, data mining and predictive analytics
• the Banking Businesses (i.e., Institutional Clients Group, Consumer, Corporate Functions) or areas of expertise (i.e. Anti-Money Laundering, Regulatory Reporting)
• Big Data analysis including big data dedicated use like HUE, Hive
• Project Management / Solution Development Life Cycle