As a Senior Machine Learning/Data Engineer at Visa's Bangalore office, you will play a pivotal role within the Global Data function, spearheading the development and management of scalable Data Science models and AI/ML pipelines. Your responsibilities will encompass the entire lifecycle of machine learning projects, from defining objectives to model deployment and optimization. Leveraging your expertise, you will ensure seamless processing of data science models at scale, contributing to Visa's mission of transforming the way the world pays.
Essential Functions
- Define and refine machine learning objectives to align with business goals.
- Develop and implement approaches for testing and training ML models using historical data.
- Build MLOps pipelines to support model development, experimentation, and deployment.
- Perform statistical analysis, interpret test results, and optimize model performance.
- Facilitate model approval process and documentation for production readiness.
- Automate deployment and training steps to streamline ML model productionization.
- Collaborate with Ops team to transition ML models into production environment.
- Solve complex data problems and optimize machine learning frameworks.
- Ensure data governance and integrity while meeting SLAs.
Qualifications
- Bachelor's degree with 4+ years of analytics experience or Master's degree with 3+ years of experience in Computer Science, Statistics, or relevant field.
- In-depth understanding of Payments and Banking Industry.
- Proficiency in PySpark, Hive, SQL, and Linux.
- Hands-on experience with Hadoop ecosystem and data processing tools.
- Strong familiarity with CI/CD frameworks and version control systems.
- Excellent communication, presentation, and collaboration skills.
- Agile working practices and program management skills.
- Ability to adapt to evolving data science tools and methodologies.
Additional Information
This is a hybrid position, offering flexibility for remote and office work. Employees are expected to work from the office 2-3 days a week, with a general guideline of being in the office 50% or more of the time based on business needs.
Join Visa's dynamic team of innovators and disruptors, and together, let's transform the way the world pays.