As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable and secure payment network - enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and is capable of handling more than 65,000 transaction messages a second. The company's dedication to innovation drives the rapid growth of connected commerce on any device, and fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network and scale to reshape the future of commerce.

At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.

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

Job Description

Role Summary
The Senior Director Data Science role sits within Visa’s Consulting and Analytics organization, focusing on the sub-region of Sub-Saharan Africa (SSA) and reporting into the VP of Data Science for CEMEA.  Core responsibilities are focused on leveraging Data Science techniques and practices into Visa’s ongoing consulting engagements with clients, which include the issuers, acquirers, and merchants that comprise the Visa ecosystem.  Additional capacity within the team is dedicated to internal functions, such as supporting the needs of the Visa Sales team, Finance, and Marketing on an as-needed basis.

The Senior Director manages the day-to-day operations of the local Data Science team, taking line management responsibility for practitioners in the field, building rapport within Visa Consulting and across other operations, and implementing the regional Data Science strategy as defined by the VP of Data Science for the region.  The most significant daily effort is spent on preparing and executing deliverables for clients, working very closely with Consulting and country leadership to shape, execute and course-correct client engagements that involve Data Science work.  In doing so, the Senior Director serves as a bridge, translating the technical practice of Data Science into the operational business realities of Visa’s clients. 

A critical measure of success is not only client satisfaction with end-deliverables from the Data Science team, but development of a robust pipeline of client work that ultimately advances and promotes Visa’s role and overarching business model within the region.  Team health, technical skills development, and facilitation of strong working relationships across Visa’s operations are other key metrics that are reviewed on a regular basis.

In CEMEA, Data Science includes responsibility for all functions supporting the end-to-end delivery of modeling work for clients, and therefore incudes oversight of ancillary functions such as Data Modeling and Analysis, Data Engineering, and Consulting itself (preparation and delivery of slide decks and client presentations). While practioners within the Visa Data Science community are largely focused on algorithm development, the Senior Director of Data Science is responsible for leveraging vendors and other Visa teams to deliver the non-core components of comprehensive client delivery within projects under his/her management.

Familiarity with financial services operations (particularly in payments) and experience in consulting is required for the role.  Technical requirements include hands-on experience with advanced analytics (predictive, classification and alternate algorithmic techniques for modeling and segmentation), prior responsibility for models running in production systems, and some machine learning and advanced AI capabilities.  Understanding of a distributed computing architecture (Hadoop) is required.  Experience in a sales-oriented role is a plus.

Visa's Data Science practice within CEMEA is fast-growing, dynamic, and collaborative.  We are required to serve a variety of clients, from large, innovative, and challenging to small and immature.  The team is a high-performing blend of advanced analytics professionals and machine learning specialists from a variety of countries, educational backgrounds, and experience. We are looking for a hands-on person who earns trust and respect of the team and the larger organization. The right person will be results-oriented while embracing strong principles of holistic leadership and people management.

Key Responsibilities

• Driving the Data Science strategy for the SSA region along with the country teams
• Subject matter expert in analytics including business problem definition, constructing analytical framework, development and validation of said framework via best statistical methodologies and implementation
• Directing and delivering multiple analytics projects along with rest of the stakeholders in Data Science & Consulting teams
• Developing analytical solutions and strategies, testing & monitoring frameworks, engaging clients, and overseeing the comprehensive deployment of said solutions
• Actively seeking out opportunities to innovate by using non-traditional data and new modeling techniques
• Collaborating with the internal teams to fully understand business requirements and desired business outcomes
• Defining detailed analytic scope and methodology, and creating analytic plan
• Providing thought leadership in both using data to solve business problems and in arriving at innovative statistical solutions
• Ensuring all project documentation is up to date and maintain the highest levels of quality in deliverables
• Ensuring project delivery within timelines and budget requirements
• Contributing to the development of the team’s analytical skills and business knowledge
• As a team lead, providing all aspects of guidance to other team members
• Cultivating open and clear communications across team members and stakeholders
• Enhancing existing analytic techniques by promoting new methodologies and best practices in the Data Science field

Qualifications

Professional

• 10+ years of analytical experience in financial industries; prior team management experience preferred 
• Subject matter expert in analytics especially in areas of analytical methodologies. Strong understanding and prior experience in Machine Learning/AI is a must
• Excellent communicator – should have the capability to translate numbers to business insights; prior experience in presenting or conducting analytics seminars or talks a big plus
• Experienced in managing multiple projects and initiatives
• Superior analytical and problem solving skills, with demonstrated intellectual and analytical rigor
• Must be team oriented, collaborative, diplomatic, and flexible, with excellent presentation skills, including strong oral and writing capabilities
• Experienced in working across a matrixed organization; multi-regional experience preferred

Technical

• Very strong project management skills and experience, preferably with a bottom-line orientation
• Ability to evaluate algorithms for contextual suitability, performance, and operational impact
• Excellent written English
• Expert level PowerPoint
• Experience and in-depth knowledge of the cards and payments business

Business

• Excellent client relationship and stakeholder management skills
• Expert in presenting ideas and analysis to stakeholders and at leadership level
• Experience in pushing new mandates for discussions and sign-offs with stakeholders
• Very detailed oriented, is expected to ensure highest level of quality/rigor in reports & data analysis
• Global mindset, desire and demonstrated ability to work cross-culturally and in a matrixed organization
• Ability to execute and solve problems independently
• Proven skills in translating analytics output to actionable recommendations, and delivery
• Multi-disciplinary thinking skills: creative, analytic, strategic

Qualifications

Professional

• 10+ years of analytical experience in financial industries; prior team management experience preferred 
• Subject matter expert in analytics especially in areas of analytical methodologies. Strong understanding and prior experience in Machine Learning/AI is a must
• Excellent communicator – should have the capability to translate numbers to business insights; prior experience in presenting or conducting analytics seminars or talks a big plus
• Experienced in managing multiple projects and initiatives
• Superior analytical and problem solving skills, with demonstrated intellectual and analytical rigor
• Must be team oriented, collaborative, diplomatic, and flexible, with excellent presentation skills, including strong oral and writing capabilities
• Experienced in working across a matrixed organization; multi-regional experience preferred

Technical

• Very strong project management skills and experience, preferably with a bottom-line orientation
• Ability to evaluate algorithms for contextual suitability, performance, and operational impact
• Excellent written English
• Expert level PowerPoint
• Experience and in-depth knowledge of the cards and payments business

Business

• Excellent client relationship and stakeholder management skills
• Expert in presenting ideas and analysis to stakeholders and at leadership level
• Experience in pushing new mandates for discussions and sign-offs with stakeholders
• Very detailed oriented, is expected to ensure highest level of quality/rigor in reports & data analysis
• Global mindset, desire and demonstrated ability to work cross-culturally and in a matrixed organization
• Ability to execute and solve problems independently
• Proven skills in translating analytics output to actionable recommendations, and delivery
• Multi-disciplinary thinking skills: creative, analytic, strategic