M
Mastercard
Senior Data Scientist (AI Engineering)
Skills
Google Cloud PlatformSQL QueriesPythonData SciencePyTorchTensorFlowDatabricksData AnalysisMachine LearningAIAWSWorkdayAzure
1 month ago
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Important information
Contract type:
Permanent
Location:
Ireland
Work mode:
Onsite
Published on:
25 September 2026
What they need
- 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 applications
- Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch
- Excellent communication and collaboration skills
- Proven experience developing and deploying machine learning solutions in production environments
- Experience working with Databricks, Spark, Azure, AWS, or GCP
- Strong expertise in machine learning, predictive analytics, statistical modelling, and experimentation
- Leadership & Communication
- Experience working in cross-functional teams to bring data science solutions from concept to deployment
- 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
- Ability to translate complex technical concepts into actionable business insights
- Strong track record of delivering measurable business outcomes through machine learning
- Advanced Python and SQL skills
- Strong analytical problem-solving skills
- Experience developing and deploying machine learning models in production environments
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
- Experience with foundation models, embeddings, or representation learning
- Experience in financial services, payments, banking, fintech, fraud, marketing analytics, or customer intelligence
- 5+ years of experience in machine learning, data science, AI, or advanced analytics
- Preferred Qualifications
- Publications, patents, conference presentations, or other evidence of technical thought leadership
- Demonstrated experience applying statistical and machine learning techniques to real-world business problems
- Master’s degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Mathematics, or a related field- End Date: August 26, 2026
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