Senior Machine Learning Scientist

Company Description

Visa is a global leader in digital payments, facilitating over 215 billion payment transactions each year between consumers, merchants, financial institutions and government entities across more than 200 countries and territories. Our mission is to connect the world through the most innovative, convenient, reliable and secure payments network, allowing individuals, businesses and economies to flourish.

When you join Visa, you become part of a culture of purpose and belonging – where your growth is our priority, your identity is valued, and your work matters. We believe in the power of inclusive economies to uplift everyone, everywhere. Your work will have a direct impact on billions of people around the world, helping to unlock financial access and shape the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

The Staff ML Scientist will work with a team to conduct exceptional research on data analytics and contribute to the long-term research agenda in large-scale data analytics and machine learning. This role offers a great opportunity to make significant contributions to Visa's strategic vision as a leading data-driven company. The successful candidate will have a strong academic record, demonstrate excellent software engineering skills, be capable of initiating projects, have a keen eye for detail, and possess outstanding collaboration skills.

Our team is working on building a new product suite for Visa’s real-time payment options! This product suite, which scales across Visa's markets, will focus on fraud management and introduce 'real-time fraud monitoring' utilizing advanced Machine Learning & Deep Learning technologies. We are seeking ML Scientists with various backgrounds who are eager to create something new and exciting for Visa.

Essential Functions

• Translate business problems into technical data challenges while ensuring key business drivers are captured in partnership with product stakeholders.
• Work with product engineering to verify the implementability of solutions. Deliver prototypes and production codes as required.
• Experiment with in-house and third-party datasets to test hypotheses about their relevance and value to business problems.
• Develop transformations on structured and unstructured data.
• Create and test modeling and scoring algorithms, including the development of custom algorithms and the application of machine learning and statistical techniques using packaged tools.
• Develop and implement methods for adaptive learning with controls on efficiency, methods for explaining model decisions where necessary, model validation, and A/B testing of models.
• Design and execute methods for effective monitoring of model efficacy and performance in production.
• Create and implement methods to automate all parts of the predictive pipeline to minimize labor in development and production.
• Contribute to the development and adoption of shared predictive analytic infrastructure.

This is a hybrid position. Employees in hybrid roles are expected to split their time between remote and office work. These employees are generally expected to be at the office on Tuesdays and Wednesdays, with an overall aim of spending about 50% of their time in the office, based on business needs.

Qualifications

Basic Qualifications:
• PhD in Computer Science, Operations Research, Statistics, or highly quantitative field with a focus on Deep Learning, Machine Learning, Data Analytics, or other mathematical analysis.
• Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks.
• Ability to code in one or more scripting languages such as Perl or Python and one or more programming languages such as Java, C++, or C#.
• Experience with one or more common statistical tools such as SAS, R, KNIME, MATLAB.
Preferred Qualifications:
• 3 years of relevant work experience with a PhD
• Familiarity with TensorFlow for deep learning is a plus.
• Experience with Natural Language Processing is beneficial.
• Familiarity with handling large datasets using tools like Hadoop, MapReduce, Pig, or Hive is advantageous.
• Publications or presentations in recognized Machine Learning and Data Mining journals/conferences are desirable.

Additional Information

Work Hours: Varies depending on the needs of the department.

Travel Requirements: This position requires 5-10% travel.

Mental/Physical Requirements: This position will predominantly involve office-based work requiring the incumbent to sit and stand at a desk, communicate in person and over the phone, and regularly operate standard office equipment like telephones and computers.

Visa is an equal opportunity employer. All 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 applicants with criminal histories in line with EEOC guidelines and local laws.

Visa will evaluate applicants with criminal histories in accordance with local laws, including the requirements of Article 49 of the San Francisco Police Code.

US APPLICANTS ONLY: The estimated salary range for a new hire into this position is between 126,000.00 and 163,800.00 USD, with potential sales incentive payments (if applicable). Salary may vary based on factors including knowledge, skills, experience, and location. In addition to the salary, this position may be eligible for bonus and equity. Visa offers a comprehensive benefits package for eligible positions that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off and a Wellness Program.