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
Data Scientist II
Role Overview
Build and productionize enterprise-grade AI and Generative AI solutions for Mastercard. This role combines strong software engineering with model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps.
Key Responsibilities
Design, develop, test, and maintain scalable AI/ML applications, APIs, and reusable engineering components.
Fine-tune and evaluate foundation models using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning.
Build RAG solutions, embeddings workflows, vector-search applications, and AI agents.
Create end-to-end ML pipelines for data preparation, training, evaluation, deployment, monitoring, and retraining.
Use Databricks, PySpark, MLflow, Unity Catalog, Workflows, Vector Search, and Model Serving for governed model development and operations.
Implement CI/CD, automated testing, observability, model monitoring, and production support practices.
Partner with data science, engineering, product, security, privacy, and governance teams to deliver reliable and responsible AI solutions.
Required Skills & Experience
3-4 years of experience in AI/ML engineering, software engineering, data science, or a related field.
Strong Python, SQL, object-oriented programming, data structures, API development, testing, Git, and software design fundamentals.
Hands-on experience with Databricks, Spark/PySpark, MLflow, model registries, and production ML workflows.
Practical AWS experience, including secure cloud architecture, container deployment, monitoring, and access controls.
Experience with PyTorch, Hugging Face, scikit-learn, FastAPI/Flask, Docker, Kubernetes, and CI/CD.
Understanding of model performance, latency, scalability, cost optimization, data quality, and responsible AI controls.
Preferred
Experience with enterprise GenAI, financial services or payments data, LangChain/LangGraph, and production-grade RAG or agentic AI systems.
Education
Bachelor's or Master's degree in Computer Science, Information Technology,or a related STEM field.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard's security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
Skills Required
- 3-4 years of experience in AI/ML engineering, software engineering, data science, or a related field
- Strong Python, SQL, object-oriented programming, data structures, API development, testing, Git, and software design fundamentals
- Hands-on experience with Databricks, Spark/PySpark, MLflow, model registries, and production ML workflows
- Practical AWS experience, including secure cloud architecture, container deployment, monitoring, and access controls
- Experience with PyTorch, Hugging Face, scikit-learn, FastAPI or Flask, Docker, Kubernetes, and CI/CD
- Understanding of model performance, latency, scalability, cost optimization, data quality, and responsible AI controls
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related STEM field
- Experience with enterprise generative AI, financial services or payments data, LangChain or LangGraph, and production-grade RAG or agentic AI systems
Mastercard Compensation & Benefits Highlights
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Retirement Support — Retirement plans are presented as best-in-class with a high company match on 401(k) or local equivalents. Career materials and U.S. postings consistently highlight retirement matching as a standout feature.
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Leave & Time Off Breadth — U.S. postings describe generous paid time off including vacation, personal days, holidays, sick/safe time, and additional bereavement leave. A hybrid policy and a limited “work from elsewhere” option further support time away.
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Parental & Family Support — Company pages state a global minimum of 16 weeks of paid new-parent leave across birth, adoption, and foster, plus family-building assistance where permitted. Mental-health resources and caregiving supports are also emphasized.
Mastercard Insights
What We Do
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.
Why Work With Us
We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.
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Mastercard Teams
Mastercard Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.






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