Director, Internal AI & Data Science - job 16 of 39

The Director, Internal AI & Data Science at Visa is responsible for leading a team of data scientists to develop and implement AI-driven products and services. This includes designing and delivering scalable data collection and integration methods for internal and external data sources, transforming data into intelligent tags, and fostering innovation within the team.

Candidates for the Director, Internal AI & Data Science position at Visa should have extensive experience in data science, expert knowledge of programming languages (such as Python and R), and familiarity with AI/ML tools. A strong background in managing teams and leading collaborative projects is also essential, alongside a strategic vision for applying data science to achieve business goals.

In the role of Director, Internal AI & Data Science, you contribute to Visa's business strategy by developing and executing plans that leverage data science capabilities to support business goals. Your insights from data will influence decision-making processes and drive innovation across various aspects of the organization.

The Director of Internal AI & Data Science at Visa should have proficiency in multiple programming languages, including Python, R, and Spark. This technical expertise is crucial for developing large-scale data science systems and executing advanced data science techniques.

The team culture for the Director, Internal AI & Data Science at Visa is one of collaboration, innovation, and continuous learning. As a leader, you will cultivate an environment where team members are encouraged to experiment and share ideas, driving both personal and professional growth.

In answering this question, focus on a project where your leadership led to significant results. Discuss the project's goals, your role, the methods used, and the outcomes achieved, emphasizing how the experience aligns with Visa's commitment to innovative data use.

Mention techniques such as establishing data verification processes, using automated testing methods, and emphasizing collaboration with data engineers to maintain data integrity throughout the project lifecycle.

Discuss your approach to leadership, including how you foster collaboration, set clear expectations, provide mentorship, and encourage a culture of innovation and continuous feedback among your team.

Talk about your commitment to professional development through webinars, conferences, and relevant literature. Describe how you apply new knowledge to your projects to ensure Visa remains at the forefront of data science innovation.

Emphasize the importance of clear communication, especially in explaining complex technical concepts to non-technical stakeholders. Provide examples of how effective communication has led to better collaboration and successful project outcomes.

Share a specific experience where you successfully integrated external data sources into your projects. Highlight the challenges faced, the techniques used for integration, and how this enriched your internal datasets.

Give an overview of your background in AI and ML, mentioning specific projects, technologies used (e.g., TensorFlow, PyTorch), and the impact of these models on business decisions, especially in the context of payment systems.

Describe your approach to project prioritization, which may include assessing business impact, resource availability, and aligning projects with strategic goals. Highlight any frameworks you use to guide your decision-making process.

Articulate your long-term vision for how data science can transform Visa's business, focusing on innovation, increased efficiencies, and improved customer experiences, while aligning these goals with Visa's overall mission and values.

Provide an example that showcases your analytical skills and ability to communicate insights effectively. Discuss how you used data to support your recommendations and the positive outcomes that followed, reinforcing your capability in impacting business decisions.