Data Scientist II

Key Skills

Data science techniques, Database, Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Pandas, Python Programming, Random forests, RNNs, SQL, TensorFlow, XGBoost

Job Description

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

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. 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

Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and therefore, it is expected that the successful candidate for this position 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.

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.