MastercardSenior Data Scientist
Mastercard is hiring a Senior Data Scientist in Gurugram, India. Level rates it ; you can apply on Mastercard.
Level's read on this job
- Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
- Tools and skills the posting cites include LangChain, MLflow and Databricks.
- Level classifies it as a senior role.
- Level lists 1,000+ other open roles at Mastercard.
- The role was posted in the last few days.
AI in this role
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
Senior Data ScientistOur PurposeMastercard 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.
Overview
The Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard’s fraud and risk product, the team builds and enhances models that analyze billions of transactions and enable real-time detection of fraudulent activity.
We are looking for a highly motivated Senior Data Scientist to help build the next generation of AI-powered fraud detection systems. This role offers an opportunity to work on challenging problems involving predictive modeling, AI agents, LLM-based solutions, real-time decisioning systems, and large-scale data engineering while contributing directly to Mastercard's mission of enabling secure and trusted commerce worldwide.
Role
As a Senior Data Scientist, you will design, develop, and deploy enterprise-scale AI solutions that enhance fraud detection and risk intelligence capabilities across Mastercard's Security Solutions portfolio.
This is not just a model development role; it is ideal for someone who enjoys working closely with complex data, exploring patterns, deeply understanding business and technical problems, experimenting through R&D, and translating practical solutions into scalable fraud and security capabilities.
Key responsibilities include:
Develop, deploy, and optimize machine learning models for fraud detection, risk scoring, anomaly detection, and related security applications.
Build scalable AI and ML pipelines supporting model training, validation, deployment, monitoring, and retraining.
Design and implement Generative AI and Agentic AI solutions leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), reasoning and planning workflows, Chain-of-Thought-style prompting techniques, tool/function calling, LLM-based modular systems, and multi-agent orchestration.
Partner with AI Engineers and Data Scientists to productionize advanced models and translate research into scalable business solutions.
Work with large-scale transactional datasets using distributed computing technologies such as Spark and Databricks.
Implement MLOps best practices, including CI/CD, model governance, observability, experimentation frameworks, and performance monitoring.
Contribute to the design of reusable AI platforms, libraries, and engineering frameworks that accelerate AI development across teams.
Evaluate emerging AI technologies and identify opportunities to apply them to fraud prevention and security challenges.
Contribute to Mastercard's innovation efforts by publishing top-tier research papers, filing patents, and translating applied AI research into scalable fraud and security solutions.
Ensure solutions meet Mastercard standards for scalability, reliability, explainability, security, and responsible AI.
All About You
Strong programming skills in Python and experience building production-quality software.
Solid understanding of machine learning fundamentals, including supervised learning, ensemble methods, feature engineering, model evaluation, and experimentation.
Hands-on experience developing and deploying machine learning solutions in production environments.
Experience working with LLMs, prompt engineering, reasoning and planning frameworks, RAG architectures, vector databases, AI agents, and Generative AI application development.
Experience with distributed computing platforms such as Spark, Databricks, or similar big data technologies.
Familiarity with cloud platforms such as Azure, AWS, or GCP and associated AI/ML services.
Understanding of MLOps principles, including model deployment, model monitoring, CI/CD, and ML lifecycle management.
Experience working with SQL and large-scale structured and unstructured datasets.
Strong analytical thinking and problem-solving abilities with a passion for solving complex real-world challenges.
Excellent communication and collaboration skills with the ability to work effectively across cross-functional teams.
Strong learning agility, intellectual curiosity, and desire to stay current with advances in AI and machine learning.
Preferred Qualifications
Experience developing fraud detection, risk management, trust & safety, cybersecurity, or financial crime solutions.
Hands-on experience with Hadoop, Spark, Databricks, MLflow, Agentic AI frameworks, reasoning and planning frameworks, LangChain, or similar AI engineering technologies.
Experience building Agentic AI solutions and multi-agent systems.
Exposure to graph learning, anomaly detection, network intelligence, or real-time decisioning systems.
Publications, patents, open-source contributions, Kaggle achievements, or demonstrated research experience in AI/ML.
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.
How we rate this
Senior Data Scientist at Mastercard rates 99 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $166k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you decide that one model's output is better than another's for a given task?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI agents, ML Ops, and AI Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. You get your review by email within 24 hours.
Get new data scientist jobs (Builds AI ●●●●) by email
One email a week with the new data scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step