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# Lead Data Scientist

- **Company:** Mastercard
- **Location:** Salt Lake City, UT, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $231,000.0
- **Contract:** Permanent contract
- **Skills:** Cyber Security, Information Engineering, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, SQL Databases, Unstructured Data, Large Language Models, Deep Learning, Pandas, Scikit Learn, Kubernetes, Information Technology, Xgboost, Virtual Agents, Text Analysis, Restful APIs, Recurrent Neural Networks, Docker
- **Published:** August 9, 2026
- **Apply:** https://www.wayup.com/i-j-Lead-Data-Scientist-Mastercard-838241767045703/

## About the Role

Substantial experience 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.
 - PhD or Master's Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.S preferred

## Description

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:

 - Experience mentoring and leading data science teams, 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.


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