Common Purpose, Uncommon Opportunity. Everyone at Visa works with one goal in mind – making sure that Visa is the best way to pay and be paid, for everyone everywhere. This is our global vision and the common purpose that unites the entire Visa team. As a global payments technology company, tech is at the heart of what we do: Our VisaNet network processes thousands of transactions per second for people and businesses around the world, enabling them to use digital currency instead of cash and checks. We are also global advocates for financial inclusion, working with partners around the world to help those who lack access to financial services join the global economy. Visa’s sponsorships, including the Olympics and FIFA™ World Cup, celebrate teamwork, diversity, and excellence throughout the world. If you have a passion to make a difference in the lives of people around the world, Visa offers an uncommon opportunity to build a strong, thriving career.

You're an Individual. We're the team for you. Together, let's transform the way the world pays.

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.

Responsibilities:

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 

Basic Qualifications

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

Preferred Qualifications

• 2+ years of work experience  and PhD in Computer Science, Operations Research, Statistics or highly quantitative field (or equivalent experience) with strength in Deep Learning, Machine Learning, Data Mining, Statistical or other mathematical analysis.
• Proficiency with object oriented programming languages, such as C++, Java, Python, and Lua.
• Experience with large scale data processing using Hadoop and MapReduce
• Strong verbal and written communication skills
• Demonstrated ability to think outside the box and innovate
• Research experience in machine learning is a plus, but not required

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.

Additional information

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.