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Director, Internal AI & Data Science - job 13 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.)
min
max
$150000K
$200000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

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

At Visa, we believe that data is the key to unlocking future growth and success! As the Director of Internal AI & Data Science based in Atlanta, you will play a crucial role in shaping how we harness the power of data to benefit consumers, businesses, and communities. Leading a talented team of data scientists, you will focus on developing AI-driven products and services, enhancing our internal datasets by integrating and processing a variety of external data sources. Your work will involve everything from designing large-scale data science systems to fostering innovation and collaboration within your team. By utilizing advanced modeling techniques, you will transform diverse data assets into actionable insights that influence critical business decisions. Your expertise in programming languages like Python and R will be invaluable as you drive our mission to create a next-generation data repository that keeps pace with evolving payment technologies. With the guidance of Visa's Chief Data Officer and collaboration with cross-functional teams, you'll lead strategic planning to align our data enrichment strategies with business goals. Join us at Visa and take the lead in driving data-related initiatives that truly make a difference in the world of payment technologies!

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

The Director, Internal AI & Data Science at Visa will oversee the design, development, and delivery of approaches for collecting and integrating both structured and unstructured data at scale. This role includes transforming data into intelligent insights using advanced modeling techniques and managing a team of data scientists to drive innovation and collaboration within the organization.

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What qualifications are required for the Director, Internal AI & Data Science position at Visa?

To excel as the Director, Internal AI & Data Science at Visa, candidates should have a strong background in data science, expertise in programming languages like Python and R, and experience with AI/ML technologies. Proven leadership skills and the ability to communicate complex concepts to stakeholders are crucial for this role, along with a passion for fostering innovation.

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How does the Director, Internal AI & Data Science contribute to Visa's data strategies?

The Director, Internal AI & Data Science plays a pivotal role in shaping Visa's data strategies by leading data-driven initiatives, collaborating with cross-functional teams, and utilizing advanced data science techniques to enrich core data sources. Their efforts directly impact decision-making and align with Visa's overall growth objectives.

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What technical skills are essential for the Director, Internal AI & Data Science position at Visa?

Essential technical skills for the Director, Internal AI & Data Science at Visa include proficiency in programming languages such as Python and R, familiarity with AI/ML tools like TensorFlow and PyTorch, and experience in designing large-scale data science systems. Expertise in data modeling and analytics is also critical.

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How does Visa support professional growth for the Director, Internal AI & Data Science?

Visa is committed to continuous learning and innovation, providing ample opportunities for professional growth for the Director, Internal AI & Data Science. This includes access to the latest data science technologies, mentoring, collaboration across departments, and a culture that encourages skill enhancement and knowledge sharing within the team.

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Common Interview Questions for Director, Internal AI & Data Science
Can you describe your experience with data science project management?

When answering this question, focus on your ability to manage timelines, coordinate team efforts, and ensure deliverables are met. Highlight specific projects you’ve led, the methodologies you’ve employed, and the outcomes achieved. Consider discussing any tools used for project tracking and collaboration.

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How do you stay updated with data science trends?

Demonstrating your commitment to continuous learning is key here. Mention resources like industry publications, online courses, conferences, and communities you engage with. Highlight specific trends or technologies you've recently explored and how they've influenced your work.

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What strategies do you use for effective collaboration with teams across different functions?

In your response, showcase your communication skills and ability to simplify complex data concepts for various audiences. Discuss examples where cross-functional collaboration led to successful data projects, emphasizing your role in fostering these relationships and driving project outcomes.

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Describe a challenging data science problem you've solved.

Select a challenging project and outline the problem, your analytical approach, and the techniques you applied to arrive at a solution. Emphasize your problem-solving process and the impact of your work, showcasing both technical and leadership abilities.

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How do you approach mentoring junior data scientists?

Discuss your commitment to mentoring by sharing your strategies for providing constructive feedback, guiding project choices, and encouraging skill development. Highlight instances where your guidance led to significant growth in a junior team member's capabilities.

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What role do you think data science plays in driving business decisions?

Articulate how data science delivers insights that directly inform business strategies and operational decisions. Use specific examples to illustrate instances where your data analysis influenced strategic direction or addressed critical business challenges.

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Can you give an example of how you've implemented a data science solution that added value?

Describe a specific project where you identified a business need, developed a data-driven solution, and demonstrated measurable results. Focus on the steps you took, the technologies you used, and the value this brought to your organization.

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What AI/ML techniques are you most familiar with?

List the techniques you have experience with, such as supervised and unsupervised learning, neural networks, or natural language processing. Provide examples of projects where you've successfully applied these techniques to solve real-world problems.

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How would you handle a situation where a project is behind schedule?

Illustrate your resourcefulness and problem-solving abilities. Describe your initial steps to analyze the causes of the delay, adjust project timelines, communicate with stakeholders, and ensure that the project remains on track moving forward.

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What are your thoughts on the ethical implications of using data in business?

Your response should reflect a thoughtful understanding of data ethics, discussing the importance of transparency, privacy, and responsible data usage. Share your experiences navigating ethical dilemmas and how you uphold data integrity in your projects.

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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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