Senior Data Scientist Job at Mastercard (Purchase)

Senior Data Scientist

Mastercard

Location:
United States , Purchase

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Finicity, a Mastercard company, is leading the Open Banking Initiative to increase the Financial Health of consumers and businesses. 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. Join our team to make an impact across all sectors of the economy by consistently innovating and problem-solving. 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.

Job Responsibility:

Develops machine-learning models to monitor open banking transactions in order to glean insights from the data and create data science algorithms to detect data anomaly observed in fraudulent transactions
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.) 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

Requirements:

5-7 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. 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

Nice to have:

Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation and credit risk modeling is a plus
SQL / Database experience is preferred
Additional Finance and FinTech experience preferred

Additional Information:

Job Posted:
May 04, 2026

Expiration:
May 29, 2026

Employment Type:

Fulltime

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