Company Description Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across 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.

　　When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

　　Join Visa: A Network Working for Everyone.

　　Job Description As a Sr. Data Engineer for Visa Research focused on Visa Risk , you will discover, and maintain a variety of research projects in the Visa Research group. In this role, you will drive innovations by introducing technologies, methods, and solutions to deliver innovative products. You will drive innovation from conceptualization to implementation. The innovation will build on machine learning, artificial intelligence, and big data research. You will research and develop flawless, fast, reliable, and secure payment solutions using foundational and applied research techniques.

　　You will engage with different collaborators, senior executives, research scientists, software engineers and architects, as well as external parties like technology vendors, wallet providers, merchants, issuers and senior product regional managers. You will discover and propose research and development opportunities, build development plan, create, and implement the ideas.

　　Our team is focusing on building a new product suite for Visa’s real time payments options! This will have a fraud-management focus and be scaled across many markets at Visa. This suite will also bring ‘real-time fraud monitoring’ into play using the latest in Machine Learning & Deep Learning technologies. We are seeking Data Engineers that come from a wide array of backgrounds with the curiosity about creating something new and exciting for Visa.

　　You will have the opportunity and the responsibility to build the long-term vision for the payment industry and influence the direction of the research and development across Visa.

　　Essential Functions:

　　Implement the set of services needed to release AI and data science models capable of working with terabytes of data. This includes model related features like one time and ongoing automatic model training, deploying, and monitoring models, as well as platform related features such as model repository, feature stores, data access layer.

　　Provide technical leadership for efforts around tooling and infrastructure that enable teams to efficiently complete and maintain data science projects.

　　Work and partner with product delivery teams to fully implement the proof of concept and early product in Visa services and products.

　　Collaborate with research scientists, product owners and architects to deliver the fast-prototyping platform.

　　Champion the innovation across the organizations and industries as an expert in the subject, either by providing consulting or by contributing to technology talks and presentations.

　　Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a detailed and timely manner.

　　Make decision on tradeoffs/priority during the design and execution, such as tradeoff between performance and flexibility, scope and timelines, availability, and scalability, etc.

　　Present and demo the research solutions to a committee on the regular basis.

　　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.

　　Qualifications Basic Qualifications:

　　• 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience

　　Preferred Qualifications:

　　• 3+ years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)

　　• Experience programming in at least one or more in Java, Python, Scala and Go

　　• Strong understanding of algorithms and data structures.

　　• Experience in leading, building and supporting scalable and reliable data solutions, AI/machine learning powered systems that can enable fast prototyping and advanced analytics using modern big data and ML/AI technologies (Hadoop, Spark, Cloud, No-SQL, TensorFlow, H2O etc.) in an agile manner.

　　• Hands-on experience developing and maintaining machine learning lifecycle: data preprocessing and feature extraction, model training and evaluation, and deployment and monitoring.

　　• Hands-on experience and/or academic background partnering with data scientists and can speak knowledgeably about the major machine learning paradigms, algorithms, and software tools.

　　• Hands-on experience and/or academic background translating data science problem statements into corresponding data, infrastructure, or workflow needs.

　　• Familiarity with the associated open-source ecosystem (e.g., mlflow, cortex, seldon, Kubeflow, tfx) is a plus.

　　• Knowledge and experience working with Frond-end web application frameworks (Angular/React) along with HTML, CSS, JavaScript is a plus.

　　• Knowledge and experience working with REST/JSON-RPC services, SQL, and NoSQL database is a plus.

　　Additional Information 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.