Data Scientist-2

Title and Summary

Data Scientist-2

Overview

The Data Science and Analytics team is looking for a Data Scientist II. The Data Science team works on Intelligent Decisioning; Financial Certainty; Attribute, Feature, and Entity Resolution; Verification Solutions and much more. The ideal candidate is passionate about leveraging data to provide high quality customer solutions. Also, the candidate is a strong technical leader who is extremely motivated, intellectually curious, analytical, and possesses an entrepreneurial mindset.

Role

Manipulates large data sets and applies various technical and statistical analytical techniques (e.g., OLS, multinomial logistic regression, LDA, clustering, segmentation) to draw insights from large datasets.

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 statement.

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.

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 analysis, vision and roadmap effectively to a wide variety of stakeholders

All about you:

3-5 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.

Additional Finance and FinTech experience preferred.

Bachelor s or Master s Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics.

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: