Sr. Data Scientist

Mastercard; Toronto; On-site; CAD 85,000 - 115,000; Full time

Job summary

A global payments technology company is seeking a highly skilled Senior Data Scientist to join their Cyber Analytics team. This role is critical in driving advanced analytics initiatives and improving fraud detection capabilities. The ideal candidate will have experience in building machine learning models and a strong understanding of data processing frameworks. This position is based in Toronto, Ontario, and offers opportunities to work on meaningful projects in cybersecurity.

Benefits

Inclusive work environment

Continuous learning opportunities

Qualifications

• Experience building machine learning models.
• Familiarity with the payment card industry and cybersecurity.
• Previous work experience in data science, ideally in related fields.

Responsibilities

• Lead data science projects focused on fraud detection.
• Develop analytical solutions including predictive models.
• Collaborate with cross-functional teams to deliver scalable solutions.
• Collaborate with cross-functional teams for scalable solutions.

Skills

Machine Learning Models in Python

Data Management

Data Mining with SQL

Cloud Platforms

Communication Skills

Cybersecurity knowledge

Quantitative analysis

Excellent communication skills

Education

Bachelor’s in Data or Computer Science or similar field

Tools

Apache Spark

Hadoop

AWS

Job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Sr. Data Scientist Overview: Mastercard services within the company are responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.

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.

All About You / Qualifications

• 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.
• 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.
• Bachelor’s in Data or Computer Science, Information Technology, Engineering, Mathematics, Statistics, or similar field.
• Recognized Data Science related certifications a plus.
• Previous work experience in data science, ideally in the payments- or cybersecurity-related industry.
• Excellent quantitative, technical, and communication skills.
• Self-motivated, curious, operates with a sense of urgency.
• Passion for Cybersecurity and profound interest in learning new tools, threat vectors, attack techniques, technologies, and best practices in preventing against cybersecurity incidents.

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [e-mail] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks come with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercards security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach;
• Complete all periodic mandatory security trainings in accordance with Mastercards guidelines.