Senior Data Scientist (AI Engineering)

Mastercard; Ireland; On-site; EUR 90,000 - 130,000; Full time

Job summary

Mastercard is seeking a Senior Data Scientist, AI Engineering to develop advanced ML solutions across domains and drive AI initiatives from concept to production. You will partner with engineering, product, and business teams to deliver measurable business impact and apply foundation-model representations for scalable outcomes.

The role emphasizes applied ML, predictive modelling, and data science with leadership and collaboration across cross-functional teams.

Qualifications

• 5+ years of experience in machine learning, data science, AI, or advanced analytics.
• Experience solving predictive modelling problems such as attrition, forecasting, recommendation systems, propensity modelling, fraud detection, risk modelling, or customer analytics
• Excellent communication and collaboration skills
• Proven experience developing and deploying machine learning solutions in production environments
• Experience with foundation models, embeddings, or representation learning
• Experience in financial services, payments, banking, fintech, fraud, marketing analytics, or customer intelligence
• Strong analytical problem-solving skills
• Ability to influence stakeholders through technical expertise and data-driven recommendations
• Experience with feature engineering, representation learning, embeddings, and downstream machine learning workflows
• Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection

Responsibilities

• Develop and deploy ML solutions across domains
• Partner with engineering, product, and business teams to productionize AI solutions
• Define modelling approaches, experimentation methodologies, and success metrics
• Apply foundation-model embeddings to improve performance
• Drive projects from problem definition to deployment and impact measurement
• Develop evaluation frameworks and benchmark new approaches
• Communicate findings to technical and non-technical stakeholders
• Mentor junior data scientists and contribute to best practices

Skills

Transformer models

ML frameworks

Python

SQL

Communication

Cross-functional collaboration

Production ML deployments

Embeddings / representation learning

Feature engineering

Statistics / modelling

Leadership

Education

Bachelor's degree in CS/DS/Math

Master’s or PhD preferred

Tools

Databricks

Spark

Azure

AWS

GCP

Job description

Responsibilities

• We are seeking a Senior Data Scientist, AI Engineering to develop advanced machine learning solutions across domains. This role combines deep expertise in predictive modelling, experimentation, and applied machine learning to deliver measurable business impact
• The successful candidate will partner closely with engineering, product, and business teams to bring innovative AI solutions from concept to production
• 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 role rather than a conversational AI, RAG, or agentic systems engineering position
• Design, develop, and deploy machine learning solutions that solve high-impact business problems
• Define modelling approaches, experimentation methodologies, 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 development, deployment, and impact measurement
• Develop robust evaluation frameworks and benchmark new approaches against existing solutions
• Partner with business, product, engineering, and analytics teams to identify and prioritise opportunities
• Communicate technical findings and recommendations to both technical and non-technical stakeholders
• Contribute to the development of best practices, reusable assets, and modelling standards across the AI organisation
• Support and mentor junior data scientists through technical guidance and knowledge sharing

Experience solving predictive modelling problems such as attrition, forecasting, recommendation systems, propensity modelling, fraud detection, risk modelling, or customer analytics

Required Technical Skills

Familiarity with transformer-based models and foundation-model applicationsExperience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorchExcellent communication and collaboration skillsProven experience developing and deploying machine learning solutions in production environmentsExperience working with Databricks, Spark, Azure, AWS, or GCPStrong expertise in machine learning, predictive analytics, statistical modelling, and experimentationLeadership & CommunicationExperience working in cross-functional teams to bring data science solutions from concept to deploymentAbility to influence stakeholders through technical expertise and data-driven recommendationsExperience with feature engineering, representation learning, embeddings, and downstream machine learning workflowsStrong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detectionAbility to translate complex technical concepts into actionable business insightsStrong track record of delivering measurable business outcomes through machine learningAdvanced Python and SQL skillsStrong analytical problem-solving skillsExperience developing and deploying machine learning models in production environmentsBachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative fieldExperience with foundation models, embeddings, or representation learningExperience in financial services, payments, banking, fintech, fraud, marketing analytics, or customer intelligence5+ years of experience in machine learning, data science, AI, or advanced analytics

Preferred Qualifications

Publications, patents, conference presentations, or other evidence of technical thought leadershipDemonstrated experience applying statistical and machine learning techniques to real-world business problemsMaster’s degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Mathematics, or a related field