Data Scientist

Mastercard is hiring a Data Scientist in New York, United States. Level rates it ; you can apply on Mastercard.

Level's read on this job

Level rates this data scientist role Builds AI ●●●●: the job is building AI systems.
The posting mentions Databricks, machine learning and predictive modeling among its tools and skills.
Level classes it as a mid-level role.
Mastercard has 948 other open roles on Level.

AI in this role

Develop predictive models and machine learning algorithms to enhance fraud detection and cybersecurity capabilities.

Databricks

machine-learningpredictive-modelingcybersecurityfraud-detectiondata-science

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re 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

Data Scientist

What is the opportunity?

We are seeking a highly skilled and motivated 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.

What will you do?

• Gain subject matter knowledge on web application security, commonly exploited cyber vulnerabilities, and methods of online and payment card fraud including the common points of purchase for compromised cards.
• 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.
• Competently handle large datasets, sifting for patterns and trends and translating those insights into technical rules and solutions.
• Combine cybersecurity and transaction data into new and insightful views of fraud and vulnerability across the Mastercard network.
• Collaborate with cross-functional teams including product, engineering, and operations to understand product, usage, and data pipelines as well as delivering scalable solutions.
• Translate clients and stakeholder needs into technical analyses and/or solutions. Communicate results and business impacts of analytical insight to senior leadership and stakeholders.
• Design metrics to track product usage, model performance and other outcomes of interest, with the aim of increasing engagement and improving the security landscape.

All About You:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Information Technology, Engineering, Mathematics, Statistics, or similar fields.
• Strong work experience in data science, ideally in the payments- or cybersecurity-related industry.
• Experienced in building statistical and machine learning models in Python and working with large-scale distributed data processing frameworks, such as Apache Spark, Hadoop and Databricks.
• Experienced in data management and data mining with SQL, optimizing performance, building data pipelines, and quantitative analysis.
• Self-starter with passion for solving problems.
• High energy level; flexible, adaptive and strong collaborator.
• Well planned, organized & structured to manage time & work effectively.
• Excellent communication skills.
• Passion for cybersecurity and profound interest in learning new tools, threat vectors, attack techniques, technologies, and best practices in preventing cybersecurity incidents.
• Previous experience with graph database and graph machine learning including graph neural network.

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 reasonable_accommodation@mastercard.com 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 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;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

Pay Ranges

New York City, New York: $110,000 - $176,000 USD

How we rate this

Data Scientist at Mastercard rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Scientist is an open job at Mastercard.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in New York City, New York.
The job was posted on September 21, 2026.
Seniority: mid.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningPredictive ModelingCybersecurityFraud DetectionData ScienceDatabricks

Also common in data scientist jobs at this level

LLM Generative AI AWS Deep learning PyTorch NLP

Pay

Typical data scientist job: $168k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where predictive modeling was part of your work. What did you do?
Tell me about a project where cybersecurity was part of your work. What did you do?
Tell me about a project where fraud detection was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine learning, Predictive Modeling, Cybersecurity, Fraud Detection, and Data Science. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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