Cyber Fraud Data Science Expert
3 hours ago
We are seeking a highly skilled Cyber Fraud Data Science Expert to join our team at Scotiabank. This is a challenging and rewarding role that requires strong analytical skills, expertise in data science and machine learning, and a passion for preventing cyber fraud.
Job DescriptionThe successful candidate will be responsible for transforming complex data into actionable insights, working with large volumes of structured and unstructured data, developing robust code using big data technologies, and employing statistical methods and machine learning techniques to enhance early detection of cyber fraud events.
Key Accountabilities:- Develop and maintain data models and structures to support advancing capabilities, creating and testing alternative methodologies and analysis techniques.
- Support the definition and tracking of key performance indicators (KPIs) related to incident management, regularly reporting on team performance and effectiveness.
- Collaborate with cross-domain data and cyber-fraud professionals to design solutions minimizing cyber-fraud events and deliver a roadmap enabling best visibility, situational awareness, and use-case automation.
To be successful in this role, you will need:
- 3+ years of data science or machine learning/engineering experience delivering high-quality analytics solutions.
- Bachelor's or Master's degree in Computer Science, Statistics, Data Science, or a related field.
- Expertise in data management best practices and deriving insights from 'big data' through on-premises and cloud tooling.
- Familiarity with incident management, threat-intelligence, customer identity and access management (CIAM), and payment card security (PCI DSS) business functions.
This role offers a competitive salary of $120,000 - $150,000 per annum, depending on experience, as well as opportunities for professional growth and development within a dynamic and inclusive organization.
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