Lead, Data Scientist
Job ID: R-244500
Location: Gurgaon, Haryana, India – 122002
Experience Required: 7–10 Years
Education: Master’s Degree Preferred in Physical Sciences / Mathematics / Statistics / Economics / Engineering or related field
Service Line: Software Engineering
Role Overview
Mastercard is seeking a Lead Data Scientist to join its Advanced Analytics team focused on Credit Risk. This role involves driving the development and deployment of data science solutions that power AI-based credit risk products. You will collaborate closely with product, engineering, and business teams to create scalable solutions that support Mastercard’s global digital economy goals.
As part of the Global Credit Risk Product team, you’ll be a key player in Mastercard’s consumer capability initiatives—developing innovative tools that leverage AI, data platforms, and real-time decisioning to enhance business impact. You will work cross-functionally and lead initiatives from concept to production with a strong focus on innovation, execution, and commercial value.
Key Responsibilities
Drive AI-based product development through data science and engineering expertise.
Apply machine learning, statistical modeling, and analytics to develop credit risk solutions.
Evaluate and implement advanced tools and techniques across the AI/ML stack.
Innovate continuously to discover new data science approaches for business challenges.
Collaborate with product, sales, and engineering to define and solve top-priority problems.
Assess technical trade-offs between alternative analytics solutions for real-world deployment.
Break down complex projects into smaller, iterative milestones to accelerate feedback and learning.
Evangelize product features, gather user feedback, and adapt future roadmaps accordingly.
Lead cross-functional team discussions to shape vision and define operating models.
Identify product improvement areas through data insights and performance analytics.
Provide technical mentorship to junior data scientists and contribute to team leadership.
Required Experience
7–10 years of hands-on experience in a Data Science function, preferably in product-focused roles.
Strong background in Machine Learning, Deep Learning, Advanced Analytics, and Statistics.
Proficiency in Python, Spark, SQL, and R.
Experience working with big data platforms such as Hadoop, Hive, Impala, or Databricks.
Demonstrated success in solving complex business problems using quantitative methods.
Strong ability to manage multiple projects, meet deadlines, and drive outcomes.
Self-motivated, flexible, and capable of leading small teams when needed.
Excellent communication, organization, and stakeholder management skills.
Creative thinking with a strong sense of curiosity and passion for innovation.
Preferred Skills
Prior experience in credit risk or financial services analytics.
Experience in launching data science-driven products from prototype to production.
Solid project management capabilities with cross-team collaboration.
Familiarity with real-time data pipelines and enterprise-grade model deployment frameworks.
