Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Analytics/Data Scientist, Launch Program 2027-India Overview Mastercard works to connect and power a sustainable and inclusive global economy. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe in connecting everyone to endless, priceless possibilities. Launch Program The Launch program is a development program that is supplemental to the role and is designed to help you transition from being a student to being a Mastercard employee. In this program, you will participate in: • Four-day orientation focused on getting to know Mastercard, building your skills, and be a force for good (Mastercard’s culture) • Professional skills workshops • Launch Innovation Week • Social impact – pro bono team challenge • Global Volunteer Challenge Role Description As a Data Scientist, you will have the opportunity to: • Gather relevant information to define the business problem. • Creative thinker capable of linking AI methodologies to identified business challenges. • Develop AI/ML applications leveraging the latest industry and academic advancements. • Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda. Qualifications • Currently enrolled in a bachelor’s or accelerated master’s program graduating between December 2026 – June 2027. • Less than 1 year of professional work experience (not including internships). • Experience or demonstrated coursework in data analysis • Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL • Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning • Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, • Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, • Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil • Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. • Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost • Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing • Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus 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. 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. Retailers want to fight fraud; we provide the tools.

Data Analytics/Data Scientist, Launch Program 2027-India.

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