Job Description

W are looking for a talented and proactive Data Scientist to join our dynamic team in the fight against financial crime. As a Data Scientist in the Group Fusion Centre, you will play a crucial role in developing and implementing advanced analytics solutions to detect, prevent, and mitigate various forms of financial crime.

• Utilize advanced statistical and machine learning techniques to analyse large volumes of financial data.
• Develop predictive models and algorithms to identify patterns and anomalies indicative of financial crime activities.
• Collaborate with cross-functional teams, including Anti-Financial Crime (AFC) units, Risk Management, and IT, to integrate data science solutions into existing systems and processes.
• Conduct exploratory data analysis to uncover insights and generate actionable recommendations for enhancing fraud detection and prevention strategies.
• Stay abreast of industry trends and emerging technologies in data science and financial crime detection, and contribute to the continuous improvement of our analytical capabilities.

Qualifications

Minimum Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field (Min)
• Post Graduate Qualification – Business Commerce or Project Management (Pref)
• Master’s or Ph.D (pref)

Experience Required:

• 3-4 years proven development experience in software and software engineering. Understanding of financial services data processes, systems, and products. Experience in technical business intelligence. Knowledge of IT infrastructure and data principles. Project management experience. Experience in building models (credit scoring, propensity models, churn)
• 3-4 years Experience in working with unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data. Experience with common data science toolkits, such as SAS, R, SPSS, etc. Experience with data visualisation tools, such as Power BI, Tableau, etc.

Additional Information

Behavioral Competencies:

• Adopting Practical Approaches
• Articulating Information
• Challenging Ideas
• Checking Details
• Examining Information
• Exploring Possibilities

Technical Competencies:

• Data Analysis
• Data Integrity
• Database Administration
• Knowledge Classification
• Research & Information Gathering