Company Description
Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in 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 while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.
Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.
Job Description
About the Team:
Visa Research is an organization that focuses exclusively on the scientific foundations of existing, emerging and future commerce-related technologies. With the establishment of a formal research organization and the associated long-term commitment to technology research, Visa joins the ranks of a small number of industry leaders with both the insight and ability to substantially influence and systemically impact the future.
The Staff 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.
Essential Functions:
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
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:
- 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.
Preferred Qualifications:
- Solid background and hands on experiences with building Machine learning, deep learning and AI models
- Experiences with Generative AI/LLM.
- Excellent understanding of algorithms and data structures and 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 working with large datasets using tools like Hadoop, MapReduce, Spark, Hive or Flink is a plus.
- Excellent analytic and problem-solving capability combined with ambition to solve real-world problems.
- 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 188,750.00 USD per year, 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.
