The Model Audit and Data Analytics (MDA) team in Internal Audit is seeking a Junior Data Scientist/Data Analytics Professional. The position is responsible for supporting the Internal Audit Division in identifying key risks and performing data analysis using data mining and visualization techniques that allow for an in-depth review of business processes, performance, and risk metrics. This role will also contribute to ad hoc data analysis to support business analytics in audits designed to determine whether risk management processes related to critical business functions and corporate quantitative models are adequate and functioning effectively.
Your Work Falls Into Three Primary Categories
- Conducting audit reviews of the organization’s financial and operational processes
- Meeting with process owners for understanding key risks, controls, systems, and data sources
- Supporting a diverse audit team in defining potential audit procedures
- Performing data analysis in support of internal audit procedures
- Extract, combine and validate structured and unstructured data from various sources, such as RDBMS (Oracle, SQL Server, DB2), flat files, SAS data sets, XML, MS Office files and Hadoop
- Apply quantitative methods to investigate and answer business questions related to risk management
- Apply statistics and machine learning methods to uncover meaningful patterns and insights in data
- Develop and maintain reproducible code for business analytics in R and Python
- Communicate business analytics findings with interactive data visualizations
Analytic Procedures and Documentation
- Documenting the results of analytic procedures in a narrative format that is easy to understand for non-technical consumers
- Preparing well written and convincing documentation and audit reports
- Coaching team members in both technical analytic skills and general audit execution
- Bachelor’s Degree in Data Analytics (Data Science), Computer Science, Quantitative Finance, Statistics, Econometrics or related field; Advanced degree is preferred.
- Typically has 1 to 3 years of experience performing data analysis using data analytics tools like R, Python, SAS, SQL, or Matlab.
- Coursework or work experience applying predictive modeling techniques from finance, statistics, mathematics, data science, and computer programming to large data sets. Qualifying course work may include--but is not limited to—statistics, mathematical programming, optimization, machine learning, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, and Monte Carlo methods/modeling.
- Experience telling stories with advanced interactive data visualizations (ggplot, matplotlib, seaborn, bokeh, plotly, d3.js, etc.)
Key to Success in this Role
- Ability to communicate and convey the insights of quantitative analysis to both technical and non-technical audiences.
- Solid oral and written communication skills. Ability to pitch and storyboard a project.
- An analytical mind that enjoys working and reasoning with data.
- Efficient programming skills in Python or R. Additional experience with SQL, SAS, Unix scripts, Java, C++, MATLAB a plus.
- Experience using version control solutions for collaborative code development (e.g., github)
- A spirit that enjoys applying innovation to business problems, combined with strong execution (owns assignments and delivers in a cross-functional setting).
- Ability to pitch and storyboard a project or user story.
- CIA, CPA, CISA certifications or interest in obtaining a certification in one of these disciplines