Digital Lead Data Scientist

1 week ago

Old Toronto, Canada MasterCard Full time
p>We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. p>

Title and Summary

Lead Data Scientist - Security Solutions

Our Purpose

Services within Mastercard is 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.

As the Lead Data Scientist, Cyber Analytics, you will be responsible for driving end-to-end data initiatives that move from model creation to tangible business value. Your primary focus will be on developing machine learning models and data pipelines that help mitigate cyber risks, while also ensuring these models are effectively integrated into products that directly serve our customers. You will work across teams—data, product, engineering, and business—to ensure your models are actionable and aligned with customer needs. If you're passionate about leveraging data science to create real-world impact and value, this role is for you.

  1. Model Development & Integration: Design, develop, and deploy machine learning models to detect, assess, and mitigate cyber risks across the Mastercard ecosystem.
  2. Customer-Focused Innovation: Contribute to product ideation by using your deep technical expertise and creativity to solve complex problems.
  3. Communication & Leadership: Lead efforts to communicate complex data science concepts and model outputs to both technical and non-technical stakeholders.

What You’ll Bring:

We’re looking for a highly skilled Lead Data Scientist who is not only an expert in building sophisticated machine learning models but also has a track record of taking those models through to product deployment, ultimately driving customer value.

Technical Expertise

  1. End-to-End Data Science Experience: Proven ability to take models from research and development to full product integration.
  2. Machine Learning Proficiency: Deep expertise in supervised and unsupervised learning, reinforcement learning, and advanced modeling techniques.
  3. Data Engineering & Pipelines: Strong experience building and optimizing data pipelines that allow seamless integration of models into production environments.
  4. Cybersecurity & Fraud Analytics: Familiarity with cybersecurity, fraud detection, and risk management processes is essential.
  5. Visualization & Reporting: Expertise in creating compelling data stories and presenting insights clearly through dashboards, reports, and visualizations.

Business Acumen & Leadership

  1. Value-Driven Mindset: Ability to align data science efforts with clear business goals.
  2. Innovation & Problem Solving: A creative thinker who is always looking for new ways to improve processes.

Qualifications

  1. Education: Advanced degree (MS or PhD) in a quantitative field such as Computer Science, Data Science, Cybersecurity, Mathematics, Statistics, Engineering, or a related discipline.
  2. Experience: Experience in data science, machine learning, or related fields, with significant experience in building and deploying models into production environments.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes 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 Mastercard’s security policies and practices;
  • Report any suspected information security violation or breach;

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