Data Scientist

PRI Global; Toronto; On-site; CAD 120,000 - 170,000; Full time

Job summary

PRI Global in Toronto, Ontario, seeks a Senior Data Scientist to join the Cyber Analytics team within the Security Solutions Data Science organization. The role focuses on driving advanced analytics, improving fraud detection, and supporting strategic decisions across cybersecurity and payment fraud domains.

You will lead data science projects, build predictive models on large data, collaborate with product, engineering, and operations, and translate stakeholder needs into actionable analyses

Qualifications

• Experience building machine learning models in Python with large-scale distributed data processing frameworks.
• Strong data management, SQL, and data pipelines.
• Familiar with cloud platforms (AWS) and fraud/cybersecurity context.
• Excellent communication and stakeholder collaboration across teams.

Responsibilities

• Lead data science projects focused on cyber analytics and fraud detection to guide strategic decisions.
• Build and maintain data-driven analytical solutions, including predictive models on large datasets.
• Identify compromised payment accounts via internal/external data feeds and analyze payment anomalies.
• Collaborate with product, engineering, and operations to deliver scalable solutions.
• Translate client needs into analyses and communicate business impact to senior leadership.

Skills

Python

Machine learning

SQL

Communication

Tools

Apache Spark

Hadoop

Playwright

Job description

We are seeking a highly skilled and motivated Senior Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. This role is critical to driving advanced analytics initiatives, improving fraud detection capabilities, and supporting strategic decision-making across cybersecurity and payment fraud domains.

Responsibilities:

• Lead data science projects focused on cyber analytics and fraud detection that will guide strategic decisions and uncover optimization opportunities.
• Build, develop, and maintain innovative data-driven analytical solutions, including predictive models and machine learning algorithms, on large volumes of data to support analytics and reporting needs across products, markets, and services.
• Identify compromised payment accounts through internal and external data feeds, scanning for anomalies in payments at merchant locations, tracking common points of purchase for compromised cards, and assessing additional data sources for value-add.
• Collaborate with cross-functional teams including product, engineering, and operations to deliver scalable solutions.
• Translate clients and stakeholder needs into technical analyses and/or solutions. Communicate results and business impacts of insight initiatives to senior leadership and stakeholders.

Requirement:

• Experienced in building machine learning models in Python and working with large-scale distributed data processing frameworks, such as Apache Spark and Hadoop.
• Experienced in data management and data mining with SQL, optimizing performance, building data pipelines, and quantitative analysis.
• Experience with cloud platforms, such as AWS, is a plus.
• Familiarity with the payment card industry, fraud, and cyber security.
• Familiarity with web crawling and scraping using Playwright or other frameworks would be a nice-to-have.
• Excellent communication, good presentation skills. Able to partner with a diverse set of stakeholders, from product to engineering to marketing and legal. Incisive understanding of customer needs.