Director, Internal AI & Data Science - job 17 of 39

The Director, Internal AI & Data Science at Visa is responsible for overseeing the design, development, and delivery of data integration processes. This role involves leading a team of data scientists to develop AI-driven models and products, transforming both structured and unstructured data into intelligent insights. Additionally, the director will communicate complex technical concepts to stakeholders, manage the team’s output quality, and foster a culture of innovation within the organization.

To be a strong candidate for the Director, Internal AI & Data Science position at Visa, applicants typically need a robust background in data science, deep understanding of AI and ML technologies, and experience with programming languages such as Python, R, and Spark. Leadership experience in managing data science teams and a track record of delivering on complex projects is also essential. An educational background in computer science, statistics, or a related field is generally preferred.

The position requires significant team management experience, specifically the ability to lead and mentor a team of data scientists. This involves ensuring high-quality deliverables, fostering collaboration and continuous learning, and inspiring innovation within the team. Effective communication skills are also vital for influencing business decisions with the data insights generated by the team.

The Director, Internal AI & Data Science plays a pivotal role in driving Visa's business strategies by leveraging data to foster informed decision-making. By enriching internal data sets and enabling sophisticated analytical capabilities, the director influences critical business insights and strategies that enhance Visa's market position and consumer relationships.

In this role, collaboration is a key component, as the Director, Internal AI & Data Science will work closely with cross-functional teams across Visa, including partnerships with the Chief Privacy Officer, Technology organization, and various business lines. This encourages a unified approach in integrating data science capabilities and sharing insights to enhance service delivery and operational efficiency.

In preparing for this question, detail specific projects where you've applied AI and ML technologies. Highlight your hands-on experience with various models, tools such as TensorFlow or PyTorch, and the impact these had on business outcomes. Use metrics to quantify achievements when possible.

Discuss your management style, providing examples of how you've successfully mentored team members. Emphasize your belief in fostering a culture of continuous learning and collaboration, and share specific strategies you've implemented to ensure team engagement and development.

Highlight your experience with data integration projects. Discuss methodologies you employ for processing and combining structured and unstructured data, including your familiarity with data engineering tools or frameworks that facilitate these integrations.

Explain your commitment to lifelong learning, whether through attending industry conferences, participating in online courses, or following key publications. Discuss recent trends in data science you find exciting and how they could potentially impact Visa’s strategies.

Be prepared to share specific case studies where your data analysis led to actionable insights that drove business impacts. Tailor your examples to illustrate how data insights you provided contributed to operational improvements or strategic pivots within an organization.

Address contemporary issues in data integration, such as handling data privacy concerns, ensuring data quality, or the complexities of merging disparate data sources. Provide thoughtful solutions or approaches you've employed to overcome those challenges.

Discuss strategies you've successfully used to simplify complex information into understandable insights for non-technical audiences. Use examples where your communication enhanced collaboration across varying levels of technical expertise.

Share your insights on advancements such as generative AI or automated machine learning. Discuss how you believe these advancements could be leveraged within Visa to enhance operations or customer interactions.

Prepare a narrative that includes project objectives, your leadership role, the methods you employed, and the results achieved. Using quantitative metrics to demonstrate success will enhance your story.

Explain your approach to prioritization, perhaps using frameworks like the Eisenhower Box or Agile methodologies. Provide examples of techniques you've implemented for effective time management in dynamic environments where multiple projects run simultaneously.