at Visa
Full TimeVisa 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.
Strategic and Functional Excellence
Good business acumen to orient data analysis to business needs of clients, including experience in the payments space.
Ability to detail out the assigned user stories with relevant implementation details and ensuring the sprint based Agile best practices are followed.
Should have strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate to stakeholders.
Good communication and presentation skills with ability to interact with different cross-functional team members at varying levels
Ability to learn new tools and paradigms as data science continues to evolve at Visa and elsewhere.
Intellectually curious and continuously striving to learn.
Technical skills
Experience with machine learning model implementation, deployment and management.
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 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 working in building and integrating the code in the defined CI/CD framework using git.
Experience in managing the operations of ML models, de-bugging issues and providing fixes.
People Leadership and Stakeholder Management
Strong interpersonal and leadership skills to influence and build credibility with senior leaders across a federated organization
Team-oriented, collaborative, diplomatic, and flexible, with proven ability to build strong working relationships with internal and external clients at all levels of management and work on complex issues within cross-functional teams
Self-starter who can responsibly advance work and is comfortable making sound, well-informed judgement calls for progress, without needless delays
An individual who is known for building deep and trusted relationships despite sometimes competing priorities
Open-minded and willing to listen to ideas and opinions from others. Able to look for new solutions when current processes don't work
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.
• 2+ years of experience leading Data/ML projects and related skills
• Fundamental and broad knowledge of common data tools and methodologies
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.
