Senior Data Scientist, Test & Learn

Mastercard Inc.; Swords; On-site; EUR 110,000 - 150,000; Full time

Job summary

Mastercard is seeking a Senior Data Scientist for its Test and Learn team to pioneer experimentation software and apply advanced data science methods to real-world business challenges. You will push analytic boundaries and translate insights into scalable products and solutions for clients globally.

The role emphasizes collaboration with product management and engineering, mentorship of teammates, and delivering high-impact analytics across high-volume data environments.

Qualifications

• 5+ years experience in data science or equivalent graduate coursework.
• Experience applying machine learning, causal inference, and/or generative AI to real world problems.
• Strong technical aptitude and business acumen to identify applications of technology to solve commercial questions.
• Experience applying innovative analytics to high volume datasets to influence business decisions.
• Excellent communication and interpersonal skills with the ability to collaborate with cross-functional teams.
• Exceptional project management and problem-solving ability with ability to manage multiple workstreams.

Responsibilities

• Drive the research of new functionality within an analytics platform used by the world’s largest organizations to support multi-million-dollar decisions.
• Work cross-functionally with product management to understand and solve customer needs requiring novel analytic solutions.
• Collaborate with engineering teams to guide the implementation of analytic ideas into Mastercard products.
• Identify problems and drive innovative solutions with business leaders across the unit.

Job description

Mastercard is seeking a Senior Data Scientist for its Test and Learn team to pioneer experimentation software and apply advanced data science methods to real-world business challenges. You will push analytic boundaries and translate insights into scalable products and solutions for clients globally.

The role emphasizes collaboration with product management and engineering, mentorship of teammates, and delivering high-impact analytics across high-volume data environments.