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Director, Internal AI & Data Science - job 33 of 39

With data being the fuel that drives our future - our strategies, policies, and business successes around data will define our future growth prospects. Unlocking the value available through the innovative use of data on behalf of consumers, businesses, and communities is key to our future. With our ongoing commitment to Visa’s Data Values and the responsible use of data, we at Visa have a bold vision to continue to grow and accelerate our data-related businesses and capabilities. 

Led by Visa’s Chief Data Officer, the Global Data Office coordinates high-impact, complex, company-wide projects related to data business strategy, critical investments, policy development, and marketplace execution. Working closely with Visa’s Chief Privacy Officer, the Technology organization, the wider data community, and the full set of Visa’s global lines of business, the Global Data Office is evolving Visa’s data-related work with momentum and enthusiasm. Driven by its commitment to trusted use of data, Visa is seeking enthusiastic leaders who are change-agents and passionate about the future of data around the world. 
The Global AI & Data Science team under the Global Data Office is focusing on how we can better create, enrich, and validate our own data sets using both internal data and external data sources, focusing on using AI and ML models to systematically collect and process data so that it can be used as a ground truth for many uses within Visa. 

In this role, you will lead a team of data scientists contributing to develop AI driven products and services, specifically focused on development of models and for collection and integration of external data sources into our own data, to be used to enrich our understanding of how Visa technologies are used to pay and be paid. The goal is to build a next-generation repository that can keep in line with the changing ways Visa credentials can be used. 

Responsibilities include:  
Overall design, development and delivery of approaches needed for collection, processing, and integration of external, structured and unstructured data at scale, into a flexible data model. 
•    Data sources include information about business across industry segments, across global markets, and spanning social media, public, and commercial databases.
•    Transforming the above data assets into a multitude of intelligent tags and personas using appropriate, scalable, modeling techniques.

Technical Leadership:
- Develop and execute a vision for data science capabilities related to enriching internal data sets
- Lead the design and development of large-scale data science systems
- Foster innovation and experimentation within the team

Team Management:
- Lead and manage a team of data scientists
- Provide guidance and mentorship to ensure high-quality deliverables
- Foster a culture of collaboration, innovation, and continuous learning

Data Science:
- Apply advanced data science techniques to drive business impact
- Stay up to date with industry trends and emerging technologies
- Develop and maintain expertise in multiple programming languages, AI/ML, GenAI/LLMs, and data science tools 

Collaboration:
- Work closely with cross-functional teams to integrate data science capabilities
- Communicate complex technical concepts and results to stakeholders
- Influence business decisions with data-driven insights

Technical Expertise:
- Develop and maintain expertise in multiple programming languages (e.g., Python, R, Spark)
- Stay current with industry trends and advancements in data science tools and technologies (e.g.,   TensorFlow, PyTorch, scikit-learn)

Strategy:
- Develop and execute a plan for enrichment of core data sources aligned with business goals
- Identify opportunities for data science to drive business impact
Communication:
- Communicate complex technical concepts and results to stakeholders
- Present data science capabilities and results to senior leadership and business partners

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Average salary estimate

$175000 / YEARLY (est.)
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$150000K
$200000K

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What You Should Know About Director, Internal AI & Data Science, Visa

Join Visa as a Director of Internal AI & Data Science in Atlanta, where your passion and expertise in data will steer our future innovations! At Visa, we believe data fuels our strategies, enabling us to accelerate growth and transform services for consumers and businesses. You'll lead a team of talented data scientists in the Global AI & Data Science team under the Global Data Office, shaping how we create, enrich, and validate data. Your focus will be on developing AI-driven products and integrating external data sources into our existing data to deepen our understanding of Visa technologies. Imagine transforming complex structured and unstructured data into intelligent personas that drive business impact! In this role, you'll design large-scale data science systems, execute a clear vision for capabilities, and foster a culture of collaboration and continuous learning amongst your team. With deep technical expertise in programming languages such as Python and R, you're already ahead of the curve. Your responsibilities include guiding and mentoring a diverse team, applying advanced data science techniques, and communicating complex ideas to stakeholders and senior leadership. If you’re ready to make a significant impact through innovative data strategies, Visa is the place for you. Let’s shape the future of data together! This hybrid position requires a flexible approach, with specific in-office days to be discussed with your hiring manager.

Frequently Asked Questions (FAQs) for Director, Internal AI & Data Science Role at Visa
What are the main responsibilities of the Director of Internal AI & Data Science at Visa?

The Director of Internal AI & Data Science at Visa is primarily responsible for leading a team of data scientists, developing AI-driven products, and creating strategies for integrating external data sets with existing internal data. This role requires overseeing the design and execution of large-scale data science systems and ensuring that advanced data techniques are employed to drive impactful business decisions.

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What qualifications do I need to apply for the Director of Internal AI & Data Science position at Visa?

To apply for the Director of Internal AI & Data Science position at Visa, candidates should ideally possess a master's degree or higher in a related field, along with substantial experience in AI, machine learning, and data science. Proficiency in programming languages such as Python, R, and familiarity with tools like TensorFlow and PyTorch is crucial, paired with experience in managing teams and projects that focus on data-driven strategies.

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How does Visa ensure the ethical use of data in the Director of Internal AI & Data Science role?

Visa establishes a commitment to responsible data use through its Data Values framework, promoting ethical practices in data management and analysis. The Director of Internal AI & Data Science collaborates with the Chief Privacy Officer to ensure that all data strategies align with these values, balancing innovation with consumer trust and data integrity.

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What skills are essential for success as the Director of Internal AI & Data Science at Visa?

Essential skills for the Director of Internal AI & Data Science at Visa include strong technical expertise in AI and machine learning, excellent leadership and team management capabilities, and the ability to communicate complex data insights effectively. Being up-to-date with industry trends and having a strategic mindset to align data initiatives with business goals are also critical for success in this role.

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What does a typical day look like for a Director of Internal AI & Data Science at Visa?

A typical day for the Director of Internal AI & Data Science at Visa involves strategizing with the data science team, reviewing project progress, mentoring employees, and collaborating with cross-functional teams. Regular communication with senior leadership to present findings and influence business decisions is also a key aspect of the role, along with staying abreast of emerging technologies and industry advancements.

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Common Interview Questions for Director, Internal AI & Data Science
Can you explain your experience with AI and machine learning in the context of data science?

When answering this question, highlight specific projects where you've applied AI and machine learning techniques to solve problems or innovate. Mention the tools and frameworks you've used, such as TensorFlow or PyTorch, and discuss the outcomes of your projects to demonstrate your impact and understanding of data science.

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How do you approach team leadership and mentoring in data science?

Discuss your leadership style and how you empower team members to identify their strengths. Talk about how you provide guidance through regular feedback, encourage collaboration, and facilitate skill development. Share examples of how you've fostered continuous learning within your team to improve their capabilities.

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What strategies do you use for integrating external data sources with internal data?

Explain your methodology for collecting and processing external data, emphasizing how you ensure compatibility with existing systems. You might want to discuss specific techniques or technologies you’ve implemented and how they enhanced the overall data integrity and insights.

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How do you stay updated on trends and advancements in data science?

Discuss the resources you utilize, such as industry publications, online courses, conferences, and networking within professional communities. Mention how staying informed impacts your decision-making and strategy within your team.

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Can you give an example of a complex data science problem you've solved?

Share a specific project where you tackled a complex problem. Detail the challenge, the solution you implemented, the tools used, and the impact it had on your organization. This shows your problem-solving skills and practical experience.

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What is your experience with presenting data-driven insights to stakeholders?

Highlight your ability to communicate complex concepts in a relatable manner. Discuss your preparation process for presentations, the type of insights shared, and any feedback received from previous stakeholders or senior leadership that illustrates your effectiveness.

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How do you promote a culture of innovation and experimentation within your team?

Talk about encouraging creative problem-solving and providing time for team members to explore new ideas. Mention any initiatives you've implemented that foster experimentation, such as hackathons or collaborative workshops, to stimulate innovation.

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What tools and programming languages are you most proficient in?

List the primary programming languages you use, such as Python and R, and any tools like Spark or scikit-learn. Highlight projects or applications where you've effectively utilized these technologies, showcasing your expertise and versatility.

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How do you handle conflicts within your team?

Share your approach to resolving conflicts, emphasizing open communication and mediation. Discuss how you ensure that all perspectives are heard and how you guide the team toward a solution that aligns with project goals and fosters a positive work environment.

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What role do you see data science playing in the broader business strategy of an organization?

Discuss the strategic importance of data science in driving business decisions, improving operational efficiency, and enhancing customer experiences. Illustrate your understanding of how data initiatives can align with business goals and create value across departments.

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Visa Inc. operates as a payments technology company worldwide. The company facilitates commerce through the transfer of value and information among consumers, merchants, financial institutions, businesses, strategic partners, and government entiti...

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Full-time, hybrid
DATE POSTED
April 3, 2025

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