Use innovative data analytics and machine learning techniques to extract valuable insights.
Identify, collect, extract data from various sources.
Perform data cleaning, wrangling, and transformation for quality analysis.
Develop and maintain efficient data pipelines for automated data processing.
Design and conduct statistical and machine learning models.
Implement predictive models to forecast outcomes and identify risks.
Collaborate with business stakeholders to add value through Data Science.
Advise and influence decision making and contribute to policy development.
Lead a team performing complex tasks and set objectives for employee coaching.
Identify ways to mitigate risk and develop new policies.

A degree in Mathematics, Statistics, Computer Science, Data Science, or a related quantitative discipline (or equivalent relevant experience).
Proven experience in fraud analytics, scam prevention, financial crime, or cybersecurity, preferably within financial services, banking, or a regulated environment.
Strong analytical and coding capabilities, with hands-on experience in Python, R, SQL, machine learning techniques, and data science frameworks to develop and enhance fraud detection models.
Experience leading, mentoring, or managing teams of data scientists, analysts, or other technical professionals.
Strong stakeholder management skills, with the ability to communicate complex analytical concepts to both technical and non-technical audiences.
Knowledge of risk management, governance, regulatory requirements, and control frameworks within a financial services environment.

Fraud Data Scientist

Key skills