Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, mid-level Data Scientist title, and broad ML skillset make applicant competition high.
Core ML/DL skills are transferable across industries, but payments and fraud domain expertise increases sensitivity to background.
Specific ML, deep learning, big-data and framework requirements raise screening rigor despite no explicit years stated.
Define business problems by gathering relevant information and linking AI methodologies to these challenges.
Develop and deploy AI/ML applications using state-of-the-art techniques and tools across Mastercard's payments and product ecosystems.
Collaborate cross-functionally and internationally to implement AI solutions that enhance operational efficiency, customer experience, and product value.
Experience Required: Not explicitly mentioned in the JD.
Proficiency in AI, Machine Learning, and Deep Learning techniques including classical models (Logistic Regression, Decision Trees, Clustering, Bayesian models) and neural networks (CNN, LSTM, GRU).
Technical skills in Python, R, SQL, Big Data platforms (Hadoop, Hive, Spark), and deep learning frameworks such as TensorFlow, Keras, PyTorch.
Concentration in Computer Science or equivalent relevant educational background.
Candidates with practical experience in AI competitions (e.g., Kaggle) demonstrating applied knowledge of AI problem-solving.
Comfortable working with large-scale data sets (10+ petabytes) and real-time transaction data for AI adoption at scale.
Experienced in collaborative, cross-border team environments to deliver innovative AI-driven business solutions.