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Data Scientist

Mastercard Open · verified Oct 24, 2026
New York Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at Mastercard. New York · full-time · $110,000–$176,000 base.

SalaryStated by Mastercard
$110,000 – $176,000
Base salary for this role, in USD per year, as published in the posting.
This role, from MastercardOur estimate for the market: $137,581–$208,900Median $157,100
The range includes the market median of $157,100 for mid-level data science roles in New York.
Worked out from 54 postings that stated pay, median $157,100. Last updated Oct 23, 2026.
RoleData Science
SeniorityMid-level
LocationNew York
EmploymentFull-time
Base pay$110,000–$176,000
PostedSep 21, 2026 · 4w ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build and maintain predictive models and machine-learning methods using large datasets for analytics and reporting
  • Find patterns in large datasets, then turn those findings into technical rules and solutions
  • Join cybersecurity and transaction data to reveal fraud and vulnerability patterns across the network
  • Work with product, engineering and operations teams to understand data flows and deliver scalable solutions
  • Set measures for product use and model results, then explain analytical findings and business impact to stakeholders

What you bring

  • A bachelor's or master's degree in data science, computer science or a related listed field
  • Substantial data science experience, ideally connected to payments or cybersecurity
  • Hands-on Python modeling experience and work with large-scale data tools such as Spark, Hadoop or Databricks
  • SQL experience covering data mining, pipeline development, performance tuning and quantitative analysis

Who this fits

This role suits a data scientist interested in cybersecurity and payment fraud, and comfortable combining transaction and security data. It is based in New York, and calls for collaboration and clear communication with technical teams and senior stakeholders.

From the employer

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

Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Science$110k+

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.