Senior Data Scientist @ Mastercard
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About Mastercard
Mastercard powers economies and empowers people in over 200 countries and territories. We support digital payments with secure, simple, and smart transactions. Our innovation, partnerships, and global networks help unlock potential for people, businesses, and governments.
Role Overview - Senior Data Scientist
Join Mastercard's AI COE in Gurgaon where you will lead AI initiatives, develop innovative models, and drive operational efficiency. You will work cross-functionally, partnering with global stakeholders to translate complex problems into practical AI solutions.
Key Responsibilities
- Own AI projects from ideation to production
- Ensure data management and privacy compliance
- Translate technical requirements for diverse stakeholders
- Develop reusable AI/ML models and solutions
- Collaborate across teams and borders
Technical Expertise & Tools
Demonstrated expertise in Data Sciences especially AI. Experience with Python, R, SQL, Hadoop, Spark, and deep learning frameworks such as Tensorflow, Keras, and PyTorch is essential. Familiarity with statistical tools and classical machine learning techniques is required.
Experience & Qualifications
6+ years experience in Data Sciences with a focus on AI. Advanced degrees and patents, experience with start-ups, and participation in competitions such as Kaggle are valued. Strong project management, communication skills and a bachelor's degree (advanced preferred) are required.
Corporate Security Responsibility
Adhere to Mastercard’s security policies, safeguard data, and complete mandatory security trainings.
Key skills/competency
- AI
- Data Sciences
- Machine Learning
- Python
- Deep Learning
- Data Management
- Big Data
- Project Management
- Stakeholder Engagement
- Innovation
How to Get Hired at Mastercard
🎯 Tips for Getting Hired
- Research Mastercard's culture: Study mission, values, news, and testimonials.
- Customize your resume: Highlight AI and data science accomplishments.
- Showcase technical skills: Emphasize Python, ML, and deep learning experience.
- Prepare clear examples: Demonstrate end-to-end project execution.