Lead analytics strategy for Mastercard's digital products, driving business growth and data - driven decisions by collaborating with global teams and stakeholders.
About the role
- Senior Data Scientist responsible for AI and data science projects at CloudPay. Collaborating on innovative payroll and HR solutions, enhancing client experiences through technology.
Responsibilities
- Own the end-to-end design, development, and deployment of high-impact AI and ML features, from prototypes to production-ready services.
- Build robust infrastructure, tools, and frameworks for training, evaluating, and serving ML models at scale, including LLMs and Generative AI solutions for both platform and customer-facing products.
- Collaborate closely with Product, Engineering, and Analytics teams to translate business requirements into actionable, production-ready AI solutions.
- Design and optimize MLOps pipelines using Databricks and cloud-native stacks (AWS Fargate, Bedrock, ECS), integrated with our newly built data platform; drive automation, monitoring, and CI/CD practices across the ML lifecycle.
- Review and validate model code, pull requests, and deployment flows, ensuring technical excellence, reproducibility, and scalability across the AI team.
- Define and align data exchange protocols and architecture with DevOps, Data Engineering, and Backend teams.
- Partner with Product Analytics to track KPIs, monitor model performance, and measure the impact of AI solutions on CloudPay products and client operations.
- Operate within cross-functional, multinational teams, with autonomy to experiment, innovate, and test new approaches while observing tangible effects on CloudPay clients and operations.
- Stay ahead of AI trends, tools, and infrastructure innovations to guide long-term strategy and maintain CloudPay’s competitive edge.
Requirements
- Proven experience as a Data Scientist, AI Specialist, or Machine Learning Engineer, preferably with a focus on NLP and Generative AI.
- Hands-on experience taking models from experimentation to production is essential.
- Strong understanding of statistical, data processing, and machine learning methods, implemented using standard open-source frameworks.
- Proven experience building production-ready ML solutions and applying MLOps best practices.
- Familiarity with AI model monitoring, evaluation, and experimentation techniques.
- Expertise in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn); knowledge of additional programming languages is a plus.
- Experience with Databricks and cloud platforms (AWS, GCP, or Azure) and scalable AI/ML solutions.
- Strong ability to translate complex business needs into actionable AI solutions.
- Experience working cross-functionally with Product, Engineering, and Analytics teams; able to clearly communicate technical concepts to non-technical stakeholders.
- Degree in quantitative field (Mathematics, Statistics, Computer Science, Physics, Engineering, or other quantitative disciplines). This is preferred NOT essential.
- Excellent written and oral communication skills in English.
Benefits
- Competitive Salary
- Competitive vacation allowance
- Calm app
- Private Medical Insurance
- EAP
- Intensive Days
- Employee Referral Program
- WFH Allowance
- Life Assurance
- CloudPay NOW
- Paid Volunteering days
- Marriage Leave
- Study Leave
- Bereavement Leave
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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