Machine Learning Scientist - Sr. Consultant level

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

The Sr Consultant ML Scientist will work with a team to conduct world-class research on data analytics and contribute to the long-term research agenda in large-scale data analytics and machine learning, as well as deliver innovative technologies and insights to Visa's strategic products and business. This role represents an exciting opportunity to make key contributions to Visa's strategic vision as a world-leading data-driven company. The successful candidate must have strong academic track record and demonstrate excellent software engineering skills. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.

The following are the group responsibilities:

• Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration product stakeholders.

• Work with product engineering to ensure implementability of solutions. Deliver prototypes and production code based on need.

• Experiment with in-house and third party data sets to test hypotheses on relevance and value of data to business problems.

• Build needed data transformations on structured and un-structured data.

• Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, data mining and statistical techniques.

• Devise and implement methods for adaptive learning with controls on effectiveness, methods for explaining model decisions where necessary, model validation, A/B testing of models.

• Devise and implement methods for efficiently monitoring model effectiveness and performance in production.

• Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.

• Contribute to development and adoption of shared predictive analytics infrastructure

• Collaborate with project team members (Product Managers, Architects, Analysts, Software Engineers, Project Managers, etc.) to ensure development and implementation of new data driven business solutions.

• Be a technical leader on various projects across the platform and be a major contributor of the entire platform’s architecture.

• Drive development effort End-to-End for on-time delivery of high-quality solutions that conform to requirements, conform to the architectural vision, and comply with all applicable coding and security standards.

• Collaborate with senior technical staff and PM to identify, document, plan contingency, 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

• Coach and mentor junior engineers on the team and help get them unblocked.

• Troubleshoot Production Issues as needed by working closely with Product and Support Teams

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:
• 8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.
• Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks.
• Ability to program in one or more scripting languages such as Perl or Python and one or more programming langu