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Director, Internal AI & Data Science - job 22 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 are pushing the boundaries of what's possible with data as we look to the future, and we're thrilled to invite a visionary Director of Internal AI & Data Science to join our Atlanta team. In this exhilarating role, you'll be at the heart of our mission, leading a talented team of data scientists dedicated to transforming how we utilize AI and machine learning to enhance and enrich our datasets. Collaborating with Visa’s Chief Data Officer and Chief Privacy Officer, you will steer high-impact projects that encompass the overall design, development, and delivery of scalable approaches for data collection and integration. Your mission? To create a next-generation data repository that evolves with the dynamic landscape of Visa technologies. We are particularly interested in your ability to harness diverse data sources—ranging from social media to commercial databases—to mold them into intelligent personas that drive our business strategies. As the technical leader, you will encourage innovation, foster a culture of continuous learning, and provide mentorship to your team, ensuring high-quality outcomes in every endeavor. Not only will you engage with cross-functional teams to communicate your insights effectively, but you’ll also have the opportunity to shape Visa’s data science standards, keeping up with industry trends and advocating for actionable, data-driven decisions. If you’re ready to be a change-agent in a fast-paced environment where your insights carry weight, we look forward to your application and to see how your expertise can further elevate Visa's data capabilities!

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?

As the Director of Internal AI & Data Science at Visa, your primary responsibilities include leading a team to develop AI-driven products and services. You'll oversee the design and delivery of scalable data collection and integration approaches, utilize both structured and unstructured data sources, and transform data into intelligent products that inform business strategies.

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What qualifications are needed for the Director of Internal AI & Data Science role at Visa?

The ideal candidate for the Director of Internal AI & Data Science position at Visa should possess advanced knowledge of data science techniques, programming languages like Python and R, and familiarity with AI/ML tools such as TensorFlow and PyTorch. A background in leading teams and communicating complex technical concepts effectively is essential.

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How does the Director of Internal AI & Data Science contribute to Visa's overall data strategy?

In the role of Director of Internal AI & Data Science, you will play a crucial role in shaping Visa's data strategy by formulating plans for enriching core data sources. Your input will directly influence decision-making processes and help align data science capabilities with broader business goals.

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What kind of team will the Director of Internal AI & Data Science at Visa manage?

The Director of Internal AI & Data Science at Visa will lead a diverse team of skilled data scientists. Your leadership will focus on fostering a culture of collaboration, innovation, and continuous learning, while providing mentorship to help the team deliver high-quality results.

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What emerging technologies should the Director of Internal AI & Data Science at Visa stay updated on?

The Director of Internal AI & Data Science at Visa should stay abreast of emerging technologies in AI and data science, including advancements in machine learning methodologies, big data processing tools, and industry trends that can impact data strategy and business operations.

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Common Interview Questions for Director, Internal AI & Data Science
Can you describe your experience leading a team of data scientists in the past?

When discussing your experience leading a team of data scientists, highlight specific examples of successfully managed projects, how you fostered collaboration and innovation, and strategies you used for mentoring team members to achieve outstanding results.

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What is your approach to integrating diverse data sources?

Explain your methodology for evaluating and incorporating various data sources, including how you assess their relevance and reliability, tools you've used for integration, and how you ensure data quality throughout the process.

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How do you stay updated with the latest trends in AI and Machine Learning?

Discuss the resources you utilize to keep informed about AI and Machine Learning, such as participating in webinars, following influential thought leaders, and engaging with professional communities in the field.

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What are your thoughts on the ethical use of data in AI systems?

Articulate your understanding of the ethical considerations involved in AI and data usage, such as fairness, transparency, and accountability, and share how you would address these concerns within your role at Visa.

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Can you share an example of how you've used data to drive business impact?

Prepare an example that demonstrates your ability to leverage data for business decisions, detailing the process, the data involved, how insights were gained, and the positive outcomes achieved for the organization.

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What tools and programming languages are you proficient in?

List the programming languages and tools you're proficient in, such as Python, R, TensorFlow, or others relevant in the data science space, and give examples of how you've used them in past projects.

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How do you ensure data quality and reliability in your projects?

Explain the practices you implement to maintain high data quality and reliability, including data validation techniques, routines for cleaning datasets, and methods for verifying the integrity of data sources.

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How do you communicate complex technical concepts to non-technical stakeholders?

Share your approach to making complex data science concepts accessible to non-technical audiences, such as breaking down the information, using visuals, and providing real-world examples to illustrate key points.

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What experience do you have with developing large-scale data systems?

Discuss your experience in developing large-scale data systems, showcasing how you've approached system architecture, the technologies utilized, and your role in managing these projects to drive results.

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What motivates you to work in the field of data science?

Reflect on your passion for data science and its potential to drive innovation and impact, sharing personal stories that fuel your enthusiasm and commitment to this dynamic field.

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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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