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 ML AI Engineer II-2 Overview Mastercard s Business Market Insights B MI group empowers organizations to achieve growth innovation goals by providing unparalleled data-driven insights and advanced analytics By leveraging proprietary data and global expertise B MI helps businesses make smarter more informed decisions that drive profitability and success We turn complex data into actionable strategies that lead to better outcomes and sustained competitive advantage We are currently looking for a Senior Engineer Machine Learning Engineering for Operational Intelligence Program within B MI group This role would entail development and delivery of secure scalable and high-performing AI ML solutions As a senior technologist this role will also focus on engineering best practices next gen innovation and stakeholder management while fostering a culture of continuous learning and technical excellence within the team Roles and Responsibilities Lead the design and development of AI and analytics solutions spanning classical machine learning time-series forecasting statistical modeling deep learning and emerging agent-based architectures Develop predictive and prescriptive models using supervised unsupervised and probabilistic approaches including regression tree-based models clustering anomaly detection Bayesian inference and ensemble methods Build and optimize time-series forecasting frameworks leveraging ARIMA SARIMA ETS Prophet VAR models state-space models LSTM GRU-based deep forecasting and ML-based hybrid forecasting pipelines for financial and operational use cases Integrate Generative AI and multi-agent systems LangGraph CrewAI AutoGen with traditional ML and statistical methods to enable reasoning-driven automation intelligent decision support and domain-aware task execution Perform exploratory data analysis feature engineering and hypothesis-driven insights using statistical testing experimental design root-cause analysis and uncertainty quantification to guide business-critical decisions Create reusable model components frameworks and evaluation workflows including model selection hyperparameter tuning cross-validation drift detection and benchmarking across classical ML and GenAI capabilities Ensure model governance explainability and responsible AI practices using interpretability frameworks SHAP counterfactuals partial dependence along with fairness transparency and compliance standards Collaborate closely with business stakeholders product teams and data engineering partners to translate domain challenges into measurable analytical solutions with quantifiable advantages and ROI Monitor performance and continuously improve production models leveraging statistical diagnostics error decomposition A B experimentation and closed-loop learning strategies Stay current with advances in machine learning statistical modeling deep learning and agentic AI evaluating emerging methods and incorporating them into future platform and capability roadmaps All About You Master s bachelor s degree in computer science or engineering and a considerable work experience with a proven track-record of successfully building complex projects products and delivering to aggressive market needs Advanced-level hands on experience designing building and deploying both conventional AI ML solutions and LLM Agentic solutions Strong analytical and problem-solving abilities with quick adaptation to new technologies methodologies and systems Strong applied knowledge and hands on experience in advanced statistical techniques predictive modelling machine learning algorithms GenAI and deep learning frameworks 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