Lead Data Scientist
@ Mastercard

Dublin, Leinster, Ireland
$150,000
On Site
Full Time
Posted 1 month ago

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Job Details

Overview

Mastercard is seeking a highly skilled and visionary Lead Data Scientist to spearhead advanced AI initiatives that drive innovation and measurable business impact. This role involves leading complex AI projects, architecting scalable machine learning systems, and mentoring a team of engineers and data scientists.

Role & Responsibilities

  • Develop AI-driven analytical solutions for business and client needs.
  • Translate stakeholder needs into technical, AI-driven solutions.
  • Design and deploy machine learning models and intelligent systems.
  • Conduct performance analyses, ad hoc reporting, and AI-powered visualizations.
  • Mentor junior colleagues and oversee technical work to ensure timely delivery.

Technical Requirements

The ideal candidate will have 5-8 years of experience in AI/ML projects, with strong proficiency in Python, TensorFlow, PyTorch, and cloud platforms such as AWS, Azure, or GCP. A deep understanding of machine learning, deep learning, NLP, MLOps, and transformer-based models (e.g., BERT, GPT, ViTs) is essential.

Corporate Security & Responsibility

All team members must adhere to Mastercard’s security policies, ensuring confidentiality, integrity, and compliance with mandatory security trainings.

Key Skills/Competency

  • Data Science
  • AI
  • Machine Learning
  • Deep Learning
  • NLP
  • Python
  • TensorFlow
  • PyTorch
  • Cloud Platforms
  • MLOps

How to Get Hired at Mastercard

🎯 Tips for Getting Hired

  • Research Mastercard's culture: Study their mission, values, and recent innovations.
  • Customize your resume: Highlight AI project leadership and technical skills.
  • Showcase real-world experience: Include advanced machine learning projects.
  • Prepare for technical interviews: Review Python, TensorFlow, and cloud fundamentals.
  • Network effectively: Connect with current Mastercard employees on LinkedIn.

📝 Interview Preparation Advice

Technical Preparation

Review Python and machine learning libraries.
Practice TensorFlow and PyTorch model deployments.
Study cloud platform integration basics.
Brush up on neural network architectures.

Behavioral Questions

Describe a challenging technical leadership scenario.
Explain your mentoring approach in tech teams.
How do you manage stakeholder communications?
Discuss a project with complex AI solutions.

Frequently Asked Questions