Sr. Data Engineer (Machine Learning)

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Essential Functions

·       Define, execute and operationalize large scale ML model solutions into production

·       Build MLOps pipelines to support development, experimentation, continuous integration, continuous delivery, verification/ validation, and monitoring of AI/ML models

• Develop processes and tools to perform model re-training, model performance evaluation and score optimization for existing ML models and troubleshoot any issues
• Be able to interpret performance evaluation results, provide alternative improvements and present the findings to other data scientist groups across regional teams

·       Build and maintain high performing ETL processes, including data quality and testing to ensure their accuracy and reliability

• Create necessary validation and documentation to support the model approval process with the Model Risk Management group to make it production ready

·       Create data dictionaries, setup/monitor data validation alerts and execute periodic jobs, ensuring timely delivery of model outputs to Visa’s clients

• Collaborate with Data engineers, Data scientists and various groups within the organization to identify areas of improvement, bottlenecks and re-use existing frameworks/processes

·       Strong understanding of development and implementation aspects of ML/AI, especially on billion-scale datasets

Technical skills:

• Very Good Understanding of  machine learning model design, implementation, deployment and management
• Experience in Automating Data Engineering and ML workflows to enhance productivity  across Data Pipelines, Preprocessing and Feature Engineering, Model Training, Evaluation, Testing, Result Generation and Monitoring
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
• Strong programming skills in building data pipelines using Python, PySpark, Hive, Airflow
• Experience working with scheduling tools (Airflow, Oozie) or building data processing orchestration workflows
• Hands-on experience working with large scale data ingestion, processing, and storage in the Hadoop ecosystem
• Experience in writing and optimizing SQL queries in Big data environment
• Experience working in Linux/Unix environment and exposure to command line utilities
• Experience creating/supporting production software/systems and a proven track record of identifying and resolving performance bottlenecks for production systems
• Experience working in building and integrating the code in the defined CI/CD framework using git.
• Experience working in machine learning models, deep learning models based on unstructured, structured, and streaming datasets
• Experience in drafting solution architecture frameworks that rely on API’s and micro-services

Strategic and Functional Excellence

• Ability to translate data and technical concepts into requirements documents, business cases and user stories
• Results-oriented with strong problem-solving skills and demonstrated intellectual and analytical rigor 
• Good business acumen with a track record in solving business problems through data-driven quantitative methodologies 
• Very detailed oriented, is expected to ensure highest level of quality/rigor in reports and data analysis 

·       Should have strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership

• Excellent written and verbal communication skills for coordinating across teams
• Demonstrated ability to incorporate new techniques to solve business problems 

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

• 5+ years of relevant work experience with a Bachelor’s Degree with specialization in Computer science, Information science, Machine Learning, Data Engineering and Analytics or relevant area.
• Exposure to Financial Services/ Payments Industry
• End to end Data Science projects, Machine learning concepts and implementation of these models at scale

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.