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Director, Internal AI & Data Science - job 38 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

As the Director of Internal AI & Data Science at Visa, based in Atlanta, you will be leading the charge in unlocking the potential of data to drive our future growth. At Visa, we believe that data is the fuel for innovation in products and services, and your role will be pivotal in shaping our data strategy. You will be at the helm of the Global AI & Data Science team, bringing together talented data scientists to develop AI-driven solutions that enhance our understanding of how Visa technologies are used globally. This includes everything from integrating structured and unstructured data to creating intelligent models that reflect market trends and consumer behaviors. Your passion for data, innovative mindset, and leadership skills will inspire your team as you work collaboratively with other departments to ensure data science capabilities are seamlessly integrated into our business processes. Your responsibilities will include crafting a vision for data enrichment, leading large-scale data initiatives, mentoring your team, and staying updated with the latest in AI/ML technologies. And yes, as a hybrid position, you will have the flexibility to balance your time between office and remote work, ensuring you have the best environment possible to excel in your role. If you're eager to make a significant impact in the fascinating world of data, Visa wants you on board!

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 be responsible for overseeing data collection, integration, and processing at scale. This role involves leading a team of data scientists to develop AI-driven products, enhancing internal datasets, and collaborating with various business segments to ensure cohesive data strategies align with Visa's business goals.

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

To successfully apply for the Director, Internal AI & Data Science role at Visa, candidates should possess a strong background in data science, including experience with programming languages like Python or R, and advanced knowledge of AI and machine learning techniques. A proven track record in leadership and the ability to manage cross-functional teams are essential.

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How does Visa's Global AI & Data Science team contribute to the company's data initiatives?

Visa's Global AI & Data Science team plays a crucial role in transforming data into actionable insights. By leveraging AI and machine learning technologies, this team is tasked with enhancing internal datasets, integrating external data sources, and ensuring that data-driven strategies are informed and aligned to drive Visa's business impact.

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What does the hybrid working model mean for the Director, Internal AI & Data Science role at Visa?

The hybrid working model for the Director, Internal AI & Data Science role at Visa means that you will have the flexibility to work both in the office and remotely. Your specific in-office days will be determined by your hiring manager, allowing you to balance collaboration with your team while enjoying the benefits of remote work.

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What opportunities for growth can the Director, Internal AI & Data Science position at Visa provide?

The Director, Internal AI & Data Science role at Visa offers immense opportunities for professional growth. You'll be at the forefront of data innovation, leading a talented team in a fast-paced environment while continuously developing your technical and leadership skills. Visa values continuous learning, ensuring that you stay current with industry trends and advancements in AI and data science.

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Common Interview Questions for Director, Internal AI & Data Science
Can you describe your experience with developing AI-driven data science models?

When answering this question, detail specific projects where you developed and implemented AI models. Emphasize your methodology, the challenges faced, and how your work positively impacted the organization. Be sure to showcase your technical proficiency and leadership in guiding teams through the AI model development process.

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How do you stay updated with the latest trends in data science and AI/ML?

For this question, mention your favorite resources such as journals, blogs, or online courses. Explain how you apply new knowledge to projects within your previous roles, showcasing your commitment to continuous improvement and innovation in the data science field.

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How would you approach the integration of external data sources into Visa's existing datasets?

Discuss your strategy for evaluating external data sources for quality and relevance. Highlight the importance of data governance and quality assurance in your process, and describe how you'd ensure data integration aligns with Visa's business objectives and maintains compliance.

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What is your leadership style when managing a team of data scientists?

Articulate a collaborative leadership approach that emphasizes mentorship, open communication, and a culture of innovation. Provide examples of how you’ve successfully led teams, fostered creativity, and achieved results through team collaboration.

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What are some of the biggest challenges you’ve faced in previous data science roles, and how did you overcome them?

Share specific challenges, such as data quality issues or resource constraints, and describe the strategies you employed to navigate these obstacles. This showcases your problem-solving skills and determination in achieving goals despite setbacks.

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Describe a successful project you led that involved large-scale data processing.

Provide details about the project scope, your role, and the outcome. Highlight technologies used, methodologies applied, and how your contribution made the project successful and added value to the organization.

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How do you prioritize tasks when leading multiple data science projects?

Discuss your process for prioritizing tasks based on impact, urgency, and resource availability. Explain how you communicate priorities with your team and stakeholders, ensuring alignment with overall business goals, and maintaining project timelines.

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What is your experience with communicating complex technical findings to non-technical stakeholders?

Describe techniques you use to simplify complex data science concepts without diluting their effectiveness. Discuss examples where you successfully presented findings to non-technical stakeholders, emphasizing the importance of clear communication in driving data-driven decisions.

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How would you ensure that the data science initiatives you lead are aligned with Visa's business strategy?

Outline an approach for keeping close collaboration with business leaders and stakeholders to understand their data needs and strategic objectives. Talk about how you’d leverage data insights to drive meaningful business decisions and impact.

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In your view, what is the future of data science and AI in the financial services industry?

Share your insights on emerging trends such as real-time data processing, predictive analytics, or responsible AI. Discuss how these advancements can shape the future of financial services, and how you see your role contributing to these changes.

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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 2, 2025

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