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 Staff ML Scientist will work with a team to conduct extraordinary 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 a phenomenal chance to create 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.

　　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 ML Scientists that come from a wide array of backgrounds with the curiosity about creating something new and exciting for Visa.

　　Essential Functions

　　Formulate business problems as technical data problems while ensuring key business drivers are collected in collaboration product stakeholders.Work with product engineering to ensure implement-ability 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, analytics, and statistical techniques.Devise and implement methods for adaptive learning with controls on efficiency, methods for explaining model decisions where vital, model validation, A/B testing of models.Devise and implement methods for efficiently monitoring model efficiency 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. 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 two days a week, Tuesdays, and Wednesdays with a general guidepost of being in the office 50% of the time based on business needs.

　　Qualifications Basic Qualifications:

　　• PhD in Computer Science, Operations Research, Statistics, or highly quantitative field with strength in Deep Learning, Machine Learning, Data Analytics, Statistical or other mathematical analysis.

　　• 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 languages such as Java, C++, or C#.

　　• Experience with one or more common statistical tools such SAS, R, KNIME, MATLAB.

　　Preferred Qualifications:

　　• 3 years of relevant experience with a PhD

　　• Deep learning experience with TensorFlow is a plus.

　　• Experience with Natural Language Processing is a plus.

　　• Experience working with large datasets using tools like Hadoop, MapReduce, Pig, or Hive is a plus.

　　• Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.

　　Additional Information Work Hours: Varies upon the needs of the department.

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

　　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.

　　Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

　　U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 130,100.00 to 169,200.00 USD, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.