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Director, Internal AI & Data Science - job 12 of 39

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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, you will be at the forefront of shaping how we leverage data to drive business success and innovation. Located in the vibrant city of Atlanta, this role places you in a dynamic environment where your expertise can unlock groundbreaking insights from our data. Your primary mission will be to lead a talented team of data scientists in developing AI-driven products and services, focusing on the integration of external data sources into our existing datasets. You'll be involved in crafting a sophisticated framework for processing a variety of data—structured and unstructured—at scale, helping Visa better understand the nuances of payment technologies across diverse global markets. With your technical leadership, you'll design large-scale data science systems and spearhead innovative projects that transform raw data into actionable intelligence. Beyond technical skills, this position requires strong team management, where mentoring and fostering a culture of continuous learning and collaboration will be key. As you stay updated with the latest trends in AI and data science, you'll work closely with cross-functional teams to influence critical business decisions, ensuring that our strategies align with Visa's mission to responsibly harness the power of data. If you are a passionate leader eager to drive the future of data at Visa, we encourage you to apply for this exciting hybrid opportunity that promises to be both challenging and rewarding.

Frequently Asked Questions (FAQs) for Director, Internal AI & Data Science Role at Visa

What are the main responsibilities of the Director, Internal AI & Data Science at Visa?

The Director, Internal AI & Data Science at Visa is responsible for leading a talented team of data scientists and developing AI-driven products. Key responsibilities include the design, development, and integration of external data sources into Visa's datasets, applying advanced data science techniques to generate business insights, and fostering a culture of innovation and collaboration within the team.