Director, Global Merchant Data
- Foster City, CA, USA
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. CyberSource, a Visa company, has been and continues to be a pioneer within the e-Commerce Payment Management world. Our VisaNet network is capable of handling over 65,000 transaction messages 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. Visa is fueled by our team of talented employees who continuously raise the bar on delivering the convenience and security of digital currency to people all over the world. Join our team and find out how Visa is everywhere you want to be.
“Visa will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of Article 49 of the San Francisco Police Code.”
Looking for an experienced product manager with extensive working knowledge of building and managing merchant data platforms. Specific responsibilities will include:
- Develop and execute on product roadmaps, works with technology and owns the strategy and key decisions throughout the product/platform development lifecycle.
- Manage multiple product needs at a time from conception to completion
- Work with internal/external customers clients to understand their strategic business requirements and lead project scoping/design to enhance the platform that serve customer needs with special focus on data quality
- Define strategy to leverage in-house and external data for effective platform/product growth.
- Drive other tasks on R&D, data governance and data quality, analytics tool evaluation, and other cross team functions, on an as-needed basis
- Ability to inspire highest level of quality/rigor/thought leadership
- Present end products, ideas, analysis at the leadership level.
- Identify new opportunities and uses of standardized merchant data to improve overall data usage experience.
- Minimum of 7+ years of product development experience in applying solutions to business problems in relevant fields such as payments industry, business consulting, or other data-driven functions.
- 5+ years of experience in planning, organizing, and managing data platforms
- Merchant data experience is strongly preferred. Analytics experience serving various industries will be a plus
- Bachelor’s degree in quantitative/relevant field such as Statistics, Operational Research, Computer Science, Economics, Business Administration, etc.
- A very strong blend of technical fluency and cutting edge business insights.
- Good business acumen to orient data analysis to business needs of clients
- Team oriented, energetic, collaborative, diplomatic, and flexible style
- Self-driven with the ability to work in a self-guided manner
- Superb communication and organization skills
- Ability to adjust to and take up different roles/responsibilities within the team, if required
- Proficiency and real-world experience in analytics tools and big data platforms including Hive/SQL, Impala, SAS, Python
- Extensive experience with SQL for extracting and aggregating data
- High level of competence in Excel, PowerPoint, and data visualization/business intelligence tools like Tableau/Microstrategy
- Familiarity or experience with data mining and statistical modeling (e.g., regression modeling, clustering techniques, decision trees, etc.) is very helpful
- Ability to apply Machine Learning/AI in real-world industrial settings with large scale data