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Mastercard is seeking a Lead Data Scientist to develop advanced AI solutions that drive innovation and deliver measurable impact across the business, by architecting scalable machine learning systems and leading complex AI initiatives.

Requirements

• Strong experience delivering data science and machine learning solutions from concept to production, including model deployment, monitoring, and performance optimization.
• Strong programming skills in Python (NumPy, Pandas, SciPy, scikit-learn) and experience with statistical modeling, predictive analytics, and data-driven experimentation.
• Hands-on experience with deep learning frameworks (TensorFlow, PyTorch) and transformer-based architectures (e.g., BERT, GPT, ViTs, etc.)
• Expertise in machine learning, deep learning, NLP, and MLOps practices (CI/CD for ML, model registry, feature stores).
• Proficiency in data engineering concepts: building scalable pipelines for batch and streaming data (Spark, Hadoop) and working with SQL/relational databases.
• Familiarity with cloud platforms (AWS, Azure, GCP) for data science workflows and model deployment.
• Skilled in data visualization and storytelling to translate complex analyses into actionable business insights.

Responsibilities

• Responsible for developing AI-driven innovative analytical solutions and identifying opportunities to support business and client needs in a quantitative and scalable manner, facilitating informed recommendations and decisions.
• Activities include designing and deploying machine learning models, building intelligent AI/Gen AI systems, conducting performance analyses, and AI-powered data visualizations.
• Lead complex initiatives and projects to derive insights and automation from AI models and systems to solve critical business questions
• Translate client/stakeholder needs into AI/Gen AI-driven technical solutions in collaboration with internal and external partners and present findings and outcomes to clients/stakeholders
• Identify rich data sources and oversee the integration, cleaning, and transformation of datasets to ensure consistency and readiness for AI applications
• Deliver high-quality AI/Gen AI solutions and tools within agreed-upon timelines and budget parameters, and conducting post-implementation reviews
• Guide others to develop sophisticated AI models and engineering solutions (e.g., intelligent agents, recommendation engines, prototypes) utilizing advanced machine learning, deep learning, and generative AI techniques

Other

• Serve as a technical coach for junior-level colleagues and develops technical talent via ongoing technical training, peer review, and mentorship
• Strong foundation in mathematics and statistics; advanced degree (Master’s or PhD) in Applied Mathematics, Statistics, Computer Science, or related field is preferred.
• Excellent communication and stakeholder management skills; ability to present findings to both technical and non-technical audiences.
• Demonstrated leadership and mentoring experience, fostering growth in technical teams and guiding research or applied projects.
• Ability to quickly learn new tools and technologies and adapt to evolving business needs.