Lead Data Scientist (AI Engineering)

Mastercard; Ireland; On-site; EUR 130,000 - 170,000; Full time

Job summary

Mastercard seeks a Lead Data Scientist, AI Engineering to lead the development of advanced ML solutions across domains. You will shape modelling strategies, drive experimentation, and deliver measurable business impact in a global payments environment.

You will mentor data scientists and AI engineers, partner with product, engineering, and analytics teams, and present findings to senior leadership. Strong track record with production ML systems and experience with foundation models, Spark,

Qualifications

• 8+ years of experience in machine learning, data science, AI, or advanced analytics.
• Strong track record of delivering measurable business outcomes through machine learning.
• Experience leading technical teams, mentoring practitioners, and influencing technical direction.
• Proven experience leading machine learning projects from concept through production deployment.
• Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Familiarity with transformer-based models and foundation-model applications.
• Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection.
• Advanced Python and SQL skills.
• Experience developing and deploying machine learning models in production environments.

Responsibilities

• Lead the design, development, and deployment of machine learning solutions that solve high-impact business problems.
• Define modelling approaches, experimentation frameworks, and success metrics for AI initiatives.
• Apply foundation-model embeddings and modern machine learning techniques to improve model performance and accelerate development.
• Drive projects from problem definition through model deployment and business impact measurement.
• Establish robust evaluation frameworks and benchmark new approaches against existing solutions.
• Partner with business, product, engineering, and analytics teams to identify and prioritise opportunities.
• Present technical findings and recommendations to stakeholders and senior leadership.
• Mentor and develop data scientists and AI engineers through technical guidance, reviews, and coaching.
• Contribute to hiring, capability development, and the long-term technical direction of the AI organisation.

Skills

Machine learning leadership

Predictive analytics

Experimentation

Communication

Stakeholder management

Mentoring

Problem solving

Cross-functional collaboration

Python

SQL

Education

Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field

Master's degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Mathematics, or a related field

Tools

Scikit-Learn

XGBoost

LightGBM

TensorFlow

PyTorch

Databricks

Spark

Azure

AWS

GCP

Job description

• We are seeking a Lead Data Scientist, AI Engineering to lead the development of advanced machine learning solutions across domains. This role combines deep expertise in predictive modelling, experimentation, and technical leadership to deliver measurable business impact
• This role focuses on applying machine learning, predictive modelling, and foundation-model representations to solve business problems at scale. Typical use cases include forecasting, propensity modelling, recommendation systems, behavioural analytics, and customer intelligence
• While familiarity with Generative AI is beneficial, this is primarily an applied machine learning and data science leadership role rather than a conversational AI, RAG, or agentic systems engineering position
• Lead the design, development, and deployment of machine learning solutions that solve high-impact business problems
• Define modelling approaches, experimentation frameworks, and success metrics for AI initiatives
• Apply foundation-model embeddings and modern machine learning techniques to improve model performance and accelerate development
• Drive projects from problem definition through model deployment and business impact measurement
• Establish robust evaluation frameworks and benchmark new approaches against existing solutions
• Partner with business, product, engineering, and analytics teams to identify and prioritise opportunities
• Present technical findings and recommendations to stakeholders and senior leadership
• Mentor and develop data scientists and AI engineers through technical guidance, reviews, and coaching
• Contribute to hiring, capability development, and the long-term technical direction of the AI organisation

• Strong track record of delivering measurable business outcomes through machine learning
• Experience solving predictive modelling problems such as attrition, forecasting, recommendation systems, propensity modelling, fraud detection, risk modelling, or customer analytics
• Experience leading technical teams, mentoring practitioners, and influencing technical direction
• Proven experience leading machine learning projects from concept through production deployment
• Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch
• Familiarity with transformer-based models and foundation-model applications
• Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection
• Strong expertise in machine learning, predictive analytics, statistical modelling, and experimentation
• Experience with feature engineering, representation learning, embeddings, and downstream machine learning workflows
• Advanced Python and SQL skills
• Experience working with Databricks, Spark, Azure, AWS, or GCP
• Leadership & Communication
• Strong problem-solving and decision-making skills
• Ability to translate complex technical concepts into actionable business insights
• Ability to lead through influence across cross-functional teams
• Excellent communication and stakeholder management capabilities
• Experience leading technical projects or teams
• 8+ years of experience in machine learning, data science, AI, or advanced analytics
• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
• Experience developing and deploying machine learning models in production environments
• Master's degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Mathematics, or a related field
• Experience in financial services, payments, banking, fintech, fraud, marketing analytics, or customer intelligence
• Experience with foundation models, embeddings, or representation learning
• Publications, patents, conference presentations, or other evidence of technical thought leadership