Lead, mentor and grow the data science team and tech stack focused on developing production-grade services and capabilities
Plan and direct data science / machine learning projects within the team.
Design and implement machine learning models for a number of financial applications including but not limited to: Transaction Classification, Temporal Analysis, Risk modeling from structured and unstructured data.
Measure, validate, implement, monitor and improve performance of both internal and external facing machine learning models.
Apply various Machine learning (i.e. SVM, Radom Forest, XGBoost, LightGBM, CATBoost etc), Deep learning techniques (i.e. LSTM, RNN, Transformer etc.) and LLMs to solve analytical problem statements.
Propose creative solutions to existing challenges that are new to the company, the financial industry and to data science.
Present technical problems and findings to business leaders internally and to clients succinctly and clearly.
Leverage best practices in machine learning and data engineering to develop scalable solutions.
Identify areas where resources fall short of needs and provide thoughtful and sustainable solutions to benefit the team
Be a strong, confident, and excellent writer and speaker, able to communicate your vision and roadmap effectively to a wide variety of stakeholders All about you:
7+ years in data science/ machine learning model development and deployments
Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation and credit risk modeling is a plus.
A strong understanding of NLP, Statistical Modeling, Visualization and advanced Data Science techniques/methods.
Gain insights from text, including non-language tokens and use the thought process of annotations in text analysis.
Solve problems that are new to the company, the financial industry and to data science
SQL / Database experience is preferred
Experience with Kubernetes, Containers, Docker, REST APIs, Event Streams or other delivery mechanisms.
Familiarity with relevant technologies (e.g. GenAI, LLMs, Agentic AI, TensorFlow, Python, Sklearn, Pandas, etc.).
Strong desire to collaborate and ability to come up with creative solutions.
Finance and FinTech experience preferred.
Bachelors or Master's Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.

S preferred 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 Salt Lake City, Utah:

$140,000

$231,000 USD Everyone wants easier ways to pay; we invent them.

Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. 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