Senior Data Engineer - Visa Research
- Austin, TX, USA
As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable and secure payment network - enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company's dedication to innovation drives the rapid growth of connected commerce on any device, and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.
At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.
You're an Individual. We're the team for you. Together, let's transform the way the world pays.
As a Senior Data Engineer for Visa Research, 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 ideation to implementation. The innovation will build on the machine learning, artificial intelligence and big data research. You will research and develop seamless, fast, reliable and secure payment solutions using foundational and applied research techniques.
You will, in many cases, interact with different stake holders, 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, create development plan, execute and implement the ideas.
You will be integral part of Visa Research team. 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.
Key responsibilities include:
- 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 support to the data science team to release Data science and AI models in production
- Provide technical leadership for efforts around tooling and infrastructure that enable teams to efficiently complete and maintain data science projects Partner with teams on modeling and analysis problems—from transforming problem statements into analysis problems
- Implement research problem solutions with prototype and early product by collaborating with other scientists, software architects and engineers
- Collaborate with research scientists, product owners and architects to deliver the fast prototyping platform.
- Conduct business and technical analysis, code reviews and unit testing, and implement and produce technical documentation of research solutions for new development, system enhancements, and production support.
- Work and partner with product delivery teams to fully implement the proof of concept and early product in Visa services and products
- Present and demo the research solutions to a committee on the regular basis
- Work with IP team to identify patent-able ideas in the research, as well as publication opportunities
- 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
- Continue to learn about the payments and technologies in Visa and across industries
- Contribute in delivery of high-quality solutions that conform to requirements and the architectural vision and comply with all applicable standards.
- Engage in requirements definition and clarification in collaboration with Business to ensure completeness and common understanding; deep understanding of the business needs is important.
- Facilitate design reviews to provide input on functional requirements, product designs, schedules, or potential problems.
- Facilitate code reviews with team members and third-party vendors. Review and assess impact of proposed scope changes on assigned deliverable(s).
- Work with other engineering teams to facilitate a common approach to continuous integration that includes build automation, test automation, and deployment automation.
- Collaborate with senior technical staff and PM to identify, document, plan contingency, and track and manage risks and issues until all are resolved.
- Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner.
- Make decision on complex tradeoffs/priority during the design and execution, such as tradeoff between performance and flexibility, scope and timelines, availability and scalability, etc.
- Master's Degree Computer Science/Computer Engineering or other technology field
- 1-3 years of work experience in areas of AI/machine learning
- Experience programming in at least one or more in Java, Python, Scala and Go
- Strong understanding of algorithms and data structures
- Experience and/or academic background building and Supporting Scalable and reliable data solutions and 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 and/or academic background developing systems for the 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.
- Very strong interpersonal, facilitation, and leadership skills along with effective communication (both written and verbal) skills and the ability to present complex ideas in a clear, concise way
- Familiarity with the associated open source ecosystem (e.g., mlflow, cortex, seldon, Kubeflow, tfx) is a plus.
- Fast learner in new technologies.
- Experience in working on large scale of distributed and hybrid system, and/or large datasets is a plus.
- Publications or presentation in recognized computing journals/conferences is a plus.
- Knowledge and experience working on Single Page Applications development, RESTful services, SQL and NoSQL databases in agile environment is a plus
- Payments industry experience is a plus.
Travel Requirements This position requires the incumbent to travel for work 5% of the time.
Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers, and reach with hands and arms.
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.