Lead Data Scientist, AI Engineering

About Mastercard

Mastercard is a global technology company operating in over 200 countries and territories. We empower the economy by enabling secure and accessible digital payment solutions. Through innovation and partnerships, we deliver a range of products and services that help individuals, businesses, and governments reach their full potential.

Role Overview

The AI Centre of Excellence at Mastercard is pioneering new AI technologies leveraging large-scale transactional data, machine learning, and foundation models. The Lead Data Scientist, AI Engineering, will spearhead the creation of advanced machine learning solutions across multiple domains, combining deep technical expertise with leadership aimed at measurable business outcomes.

Key Responsibilities

• Lead end-to-end development, from design to deployment, of machine learning models addressing significant business challenges.
• Define modelling methodologies, experimentation strategies, and metrics to gauge the success of AI projects.
• Utilize foundation-model embeddings and cutting-edge machine learning techniques to enhance model effectiveness and speed up development.
• Oversee projects through all phases including problem identification, model deployment, and impact evaluation.
• Develop rigorous evaluation frameworks and benchmark novel approaches against existing solutions.
• Collaborate closely with business, product, engineering, and analytics teams to spot and prioritize opportunities.
• Communicate technical insights and strategic recommendations to senior leaders and stakeholders.
• Support the growth and development of data scientists and AI engineers through mentorship, reviews, and coaching.
• Participate in recruitment, capability building, and shaping the AI team's technical vision.

Required Qualifications and Skills

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative discipline.
• Minimum of 8 years’ experience in machine learning, advanced analytics, or AI, including leading projects from concept to production.
• Proficient in Python and SQL programming.
• Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Expertise in classification, regression, forecasting, recommendation systems, ranking algorithms, clustering, and anomaly detection.
• Hands-on experience with feature engineering, representation learning, embeddings, and related machine learning workflows.
• Familiarity with transformer architectures and foundation-model implementations.
• Experience leveraging big data platforms such as Databricks, Spark, Azure, AWS, or Google Cloud Platform.
• Strong problem-solving, decision-making, communication, and leadership abilities, with a track record of guiding cross-functional teams and translating complex technical subjects for business audiences.

Preferred Qualifications

• Advanced degree (Master’s or PhD) in Machine Learning, AI, Computer Science, Statistics, Mathematics, or related fields.
• Experience working in financial services, payments, banking, fintech, fraud detection, marketing analytics, or customer intelligence domains.
• Demonstrated technical leadership through publications, patents, or conference contributions.

Security and Compliance

• Adherence to Mastercard’s security policies to ensure data confidentiality and integrity.
• Obligation to report any suspected security breaches.
• Completion of mandatory security training as per organizational guidelines.