Director, Internal AI & Data Science - job 18 of 39

The Director, Internal AI & Data Science at Visa is responsible for leading a team of data scientists in the design and development of large-scale data systems. This includes overseeing the enrichment of internal data sets through advanced AI and ML techniques, strategizing on the integration of external data sources, and fostering a culture of innovation and collaboration within the team. Additionally, you will communicate complex data science concepts to stakeholders and influence business initiatives through data-driven insights.

To qualify for the Director, Internal AI & Data Science position at Visa, candidates typically need extensive experience in data science and team management. A strong background in programming languages like Python and R, as well as proficiency with AI/ML tools such as TensorFlow and PyTorch, is essential. Additionally, having a strategic mindset, leadership experience, and the ability to communicate complex ideas effectively to a variety of stakeholders is crucial for success in this role.

The Director, Internal AI & Data Science plays a vital role in shaping Visa's data-related strategies by leading efforts to enhance data processing and integration. This includes transforming both existing and new data into actionable insights through innovative AI models, aligning data initiatives with broader business goals, and fostering cross-functional collaboration to implement data-driven solutions that drive business impact.

Collaboration is fundamental for the Director, Internal AI & Data Science at Visa, as you'll work closely with cross-functional teams to integrate advanced data science capabilities into various business sectors. Strong collaboration with stakeholders ensures that insights derived from data influence strategic decisions, while also aligning data projects with the overarching goals of Visa, enabling innovation and enhancing operational effectiveness across the organization.

The Director, Internal AI & Data Science at Visa might face challenges such as keeping pace with rapidly evolving AI and data science technologies, integrating diverse data sources effectively, and ensuring responsible data usage that aligns with Visa’s commitments. Additionally, managing a team of skilled data scientists and fostering innovation while navigating through complex organizational structures can present unique challenges in this role.

To develop a strategy for enriching Visa's internal data sources, I would start with a thorough analysis of existing data sets to identify gaps and opportunities. Collaborating with cross-functional teams would help to determine what additional data sources are valuable. I would also prioritize scalable AI techniques for data integration and ensure alignment with Visa's business objectives, continuously iterating based on feedback and new data insights.

I have extensive experience in leading data science teams, where I focus on empowering team members through mentorship and fostering an innovative work environment. My approach includes setting clear expectations, encouraging collaboration, and promoting continuous learning. I've successfully managed team dynamics to ensure high-quality deliverables while also engaging in strategic project planning to guide the team towards impactful outcomes.

Certainly! In my previous role, I led a project that integrated multiple external data sources into our internal databases to enhance customer insights. By applying advanced machine learning models, we were able to transform raw data into intelligible business metrics, which ultimately improved decision-making processes and drove revenue growth by 20%. The project showcased how effective data integration can lead to significant business impacts.

I stay updated by subscribing to industry publications, attending relevant conferences, and participating in online data science communities. Additionally, I invest time in hands-on practice with emerging technologies and tools, ensuring that I not only understand theoretical advancements but also practical applications, which helps me lead my team with current best practices.

I am proficient in several programming languages including Python, R, and SQL, which are foundational for data manipulation and analysis. I also have extensive experience with Jupyter notebooks and tools like TensorFlow and PyTorch for machine learning. This proficiency allows me to guide my team effectively and contribute to the technical aspects of data-focused projects.

In a previous project, I analyzed customer behavior patterns to uncover insights that indicated a shifting preference toward digital payment methods. I presented these findings to senior management, emphasizing the necessity for enhanced digital solutions. This prompted a strategic pivot that resulted in a successful new product launch, increasing our market share significantly.

To ensure data integrity and quality, I implement a comprehensive data validation framework that includes regular audits and automated checks. I also promote a culture of data responsibility within my team, encouraging meticulous data handling practices. Collaboration with data ownership teams ensures that we align on data governance policies, which is crucial for maintaining high-quality datasets.

My approach to mentorship involves personalized guidance based on each team member's strengths and areas for growth. I prioritize knowledge sharing through regular workshops, code reviews, and collaborative project work. By creating an open environment where team members feel safe to experiment and ask questions, I foster a culture of continuous learning and professional development.

I have successfully managed several projects that involved integrating external data sources into internal databases. This requires careful consideration of data formats, privacy concerns, and technical compatibility. I ensure that integration processes are scalable and efficient, employing ETL processes to maintain data quality while enriching our internal repositories.

I prioritize projects based on a combination of business impact, resource availability, and strategic alignment with company objectives. I discuss priorities with stakeholders to ensure alignment and adjust as necessary based on changing business needs. Regular check-ins with the team help to keep projects on track and ensure we are focused on delivering value.