Data Scientist II
Mastercard · Gurgaon
- Experience3–4 yrs
- SalaryNot disclosed
- Work modeonsite
- Levelmid
- Posted22 Sept 2026
About Mastercard
Mastercard is hiring in Gurgaon in financial services. This role looks for around 3+ years of experience.
Skills
- Python
- SQL
- Object-Oriented Programming
- Data Structures
- API Development
- Git
- Software Design
- Databricks
- Apache Spark
- PySpark
- MLflow
- Model Registries
- AWS
- Secure Cloud Architecture
- Container Deployment
- Monitoring
- Access Controls
- PyTorch
- Hugging Face
- scikit-learn
- FastAPI
- Flask
- Docker
- Kubernetes
- CI/CD
- Model Performance
- Latency
- Scalability
- Cost Optimization
- Data Quality
- Responsible AI
The role
A generative AI engineer at a digital payments company builds enterprise AI solutions and productionizes foundation models through RAG systems and Databricks. The work combines MLflow with AWS deployment and governed MLOps for secure, scalable model operations.
Full job description
Our Purpose
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
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.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.