Senior Data Scientist

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

Senior Data Scientist

Overview
The Foundational AI team is looking for a Data Scientist who is passionate about applying concepts from Topological Data Analysis (TDA) to Machine Learning and Artificial Intelligence problems in a business setting. The person in this role will be joining a team of leading-edge data scientists who are not just building models but are working to solve foundational business problems for the Company while making scientific contributions to the Data Science community.

The ideal candidate is comfortable with Topological Data Analysis concepts like Persistent Homology and applying them to Big data sources, predictive, and descriptive models to provide insights and solutions for different business problems. The person in this role will be responsible for data interpretation and presentation to aid business partners in making informed data-driven decisions to improve business outcomes. The right candidate is able to collaborate with other data scientists and various internal business partners to help solve business problems using advanced ML/AI and TDA. The person in this role must be organized and follow best practices in coding and documentation.

Responsibilities:
• Design, develop and deliver innovative ML/AI solutions for various data science projects.
• Be responsible for documenting and articulating various data science projects across the organization following our engagement model, the Cross-Industry Standard Process for Data Mining (CRISP-DM).
• Gain a clear understanding of business operations and data needed to solve problem statements for specific projects.
• Pull and prepare data, train and test models, and be responsible for overall execution on projects using Mastercard operational and transaction data to glean insights for our partners.
• Present your approach to the solution and model output to various business partners.
• Maintain a curent knowledge of advanced TDA and ML/AI tools and techniques.
• Work with different product teams and be an integral part of model deployment.
• Need to build and maintain strong relationships with internal Mastercard partners.

About You
• Education in a highly quantitative field (mathematics, statistics, computer science, or related fields).
• Having a passion for problem solving using mathematics, statistics, machine learning, and artificial intelligence.
• Ability to quickly pick up new tools and technologies.
• Excellent oral and written communication skills.
• Proficiency in Python/R, Hadoop, Spark, MySQL with documentation for reproducibility.
•. Experience in anomaly detection, supervised/unsupervised learning, time-series data, and natural language processing. Experience in entity resolution is a plus
• Hands-on experience with python packages such as Gudhi, Prism, Ripser, Numpy, SciPy, Pandas, Scikit-learn, Tensorflow, Keras, NLTK, Gensim, BERT, NetworkX, etc.
• Excellent organization and interpersonal skills.
• Strong problem-solving skills, detail-oriented and ability to think creatively with data.
• Self-motivated and capable of working independently but with a collaborative nature.
• Proficient with data visualization and translating complex problems into actionable insights.

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 [email protected] 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.