Senior Associate, Data Scientist for Internal Audit (10566)

Reporting to the Managing Director of Assurance, the incumbent will assist the assurance team members to achieve greater risk coverage, stronger assurance and deeper business insights through the use of data science.

Responsibilities:

• Analyze structured and unstructured data to generate actionable insights to enhance risk and control activities.
• Collaborate with the Digital Technology team to develop data connectors and machine learning models to analyze structured and unstructured data, and generate actionable insights
• Work with large and complex datasets and develop comprehensive knowledge of data structures and metrics.
• Solve difficult, non-routine issues with data analysis by applying advanced analytical methods as needed
• Work closely with business stakeholders to analyze large data sets, apply machine learning algorithms to optimize data-driven operational risk decisions
• Interact cross-functionally with technology team for productization (e.g., dashboards, automation bots, website, mobile apps) with effective presentations of findings through visual displays of quantitative information.
• Research and develop analysis to optimize the previous data solutions.
• Keep abreast of market developments in data analytics and recommend best practices for adoption

Requirements:

• Bachelor's degree in Computer Science, Information Systems, or relevant quantitative fields.
• Minimum 3 years of experience in creating and using machine learning algorithms, data minimg, building statistical models, manipulating data sets and end-to-end process from ETL, modelling to result validation.
• Proficient in at least two data/statistics programming languages (Python/R/MATLAB/SAS), and familiar with database languages (SQL/Graph);
• Good understanding with NLP, anomaly detection, and other common machine learning techniques.
• Highly proficient in Python and working experience with Python based data workflows.
• Knowledge of dashboard creation and visualization using Tableau
• Strong analytical and organization skills, with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Self-motivated and driven, able to work independently on technical projects.
• Demonstrated skills in selecting the right statistical tools to meet data analysis requirements. Demonstrated good logical thinking and the ability to quickly learn and understand new business processes, and how to apply data techniques.
• Willingness to both teach others and learn new techniques. Effective written and verbal communication skills.