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Senior Data Scientist

Gurgaon, Haryāna, India

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What you’ll work on

Full posting
  • Develop and deploy ML models for fraud detection, risk scoring and anomaly detection

  • Build scalable AI and ML pipelines for training, validation, deployment and retraining

  • Design Generative AI and agentic AI solutions using LLMs and RAG

  • Work with large transactional datasets using Spark and Databricks

  • Implement MLOps practices including CI/CD, governance and performance monitoring

From the employer’s posting
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)
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.

What you’ll bring

All qualifications

Preferred experience

  • 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.
Qualification wording
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.
Apply at Mastercard

Posting record

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Status in our records
Live
First seen by us
Nov 3, 2026today
Recorded sightings
2
Last seen by us
Nov 4, 2026
Reposted
once since Oct 27, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 7 and day 55.

From 9,971 similar postings that came down. Coming down is not always a hire.

Mastercard is hiring

80 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring is steady
  • Takes jobs down at a usual pace
  • 8% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • GCP
  • Hadoop
  • MLflow
  • Spark
Where the posting names them
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.
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.
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.
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.
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.
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.

Your next step

Complete your application on mastercard.wd1.myworkdayjobs.com. The employer’s form will show what is required.

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Has Mastercard posted this job before?

Yes. We’ve followed 6 other Senior Data Scientist jobs there since April 2026. 5 came down, usually after about 38 days. One is still up.

  1. Salt Lake CityCame down after 61 days, first seen Apr 16
  2. GurugramCame down after 40 days, first seen May 6
  3. PuneCame down after 16 days, first seen Aug 14
  4. LondonCame down after 38 days, first seen Sep 17
  5. GurugramCame down after 29 days, first seen Sep 22
  6. DublinStill up after 7 days, first seen Oct 28
  7. This jobUp 1 day so far, first seen Nov 3

If this one keeps the same pace, it may come down around December 11.

Large employers often post one title for several teams, so these can be separate openings.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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 Scientist

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.

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.




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Gurgaon, Haryāna, India

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