Role at a glance
- Job function
-
AI & Data Data Science
- Salary
- Not Disclosed
- Location
- Gurgaon, India
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 3–4 years of experience in AI/ML engineering, software engineering, data science, or a related field.
- Education
- Bachelor’s or Master’s degree in Computer Science, Information Technology,or a related STEM field.
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Role Summary
The Data Scientist II builds and productionizes enterprise-grade AI and Generative AI solutions for Mastercard. The role combines software engineering, model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps to deliver reliable and responsible AI solutions.
What You'll Do
- 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.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
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, production ML workflows, AWS, PyTorch, Hugging Face, scikit-learn, FastAPI/Flask, Docker, Kubernetes, and CI/CD.
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/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
Preferred
- Experience with enterprise GenAI, financial services or payments data, LangChain/LangGraph, and production-grade RAG or agentic AI systems
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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 IIRole OverviewBuild 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.
About the company
Mastercard
Large Enterprise
Mastercard is a global technology company in the payments industry, committed to empowering individuals and businesses through secure and efficient payment solutions. With a presence in over 210 countries, Mastercard connects consumers, financial institutions, merchants, and governments, enabling seamless transactions across various platforms. The company is at the forefront of innovation, focusing on enhancing financial inclusion and expanding access to digital payment technologies. Through its advanced network and partnerships, Mastercard continues to revolutionize the way people engage in commerce worldwide.