Senior Analyst, Data Strategy

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 Senior Analyst, Data Strategy Senior Analyst, Data Strategy The Enterprise Data Quality (EDQ) team within the AI and Data Office is responsible for developing Mastercard’s data quality program and driving data quality improvements. We ensure data is of the highest quality and is fit-for-purpose to support business and analytic uses. Data Sourcing will support the data sourcing strategy leading the acquisition and analysis of third-party data to support business use cases and product development. This role focuses on implementing data quality and remediation priorities and delivering solutions using SQL, python, AI/ML tools, and cloud-based platforms. Working closely with data quality team, data collection and compliance teams, technical teams, and business stakeholders, the Senior Analyst ensures high-quality external data is integrated effectively in MasterCard global data sets. Role As Senior Analyst, Data Strategy you will: • Design, build, and deploy machine learning and AI-driven solutions to support the execution of data quality and remediations strategies by partnering with Data quality team, data collection and compliance team, business SMEs, and stakeholders to understand requirements, evaluate and deliver insights for high-quality output. • Lead the development of machine learning models supporting data quality improvement use cases across forecasting, optimization, NLP, computer vision, and generative AI • Remediation models across cloud and on-prem systems, while co-driving data quality strategies and keep improving MasterCard data sets. • Perform data analysis using Python, SQL, cloud tools, and workflow automation platforms; iterate on outputs and share actionable insights with stakeholders. • Apply governance standards during execution to ensure compliance with privacy regulations. • Shape strategic data sourcing decisions by supporting requirement gathering, validating use cases, and advising on data suitability for enterprise initiatives • Collaborate with technical teams to run workflows and monitor pipeline performance. • Contribute to modernization efforts by recommending improvements to data processes, governance, and security features that enable advanced analytics and innovation. • Develop educational materials and provide training on tools and processes as needed. All About You • Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, Engineering, or related field. • Strong expertise in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow). • Experience developing and deploying ML models in production. • Knowledge of LLMs, embeddings, prompt engineering, and vector databases. • Solid understanding of cloud platforms (Azure/AWS/GCP), SQL, and distributed data systems. • Familiarity with MLOps, CI/CD, and model monitoring. • Experience in generative AI and agents’ development with scalability • Experience working in enterprise data strategy or large-scale data environments. • Hands-on with Azure OpenAI, Databricks, or Snowflake ML. • Background in forecasting, customer analytics, risk modelling, or operational optimization. • Understanding of data governance, metadata management, and data quality frameworks. • Experience developing reusable ML components or accelerators. • Strong communication and stakeholder-management skills. • Ability to simplify complex AI/ML topics for non-technical audiences. • Strategic mindset with the ability to balance long term arch ... (truncated, view full listing at source)