Job details

Director, Internal AI & Data Science - job 26 of 39

Get a free resume review

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

As the Director of Internal AI & Data Science at Visa in Atlanta, you'll be at the forefront of innovation, leveraging the power of data to propel the company into the future. With data being a vital asset, your mission will consist of designing and executing strategies that enrich our data sets using both internal and external sources through advanced AI and ML models. Imagine leading a talented team of data scientists dedicated to transforming structured and unstructured data into actionable insights that will enhance how Visa's technologies are used. You'll orchestrate the overall design and delivery of technical solutions that facilitate seamless data collection processes while collaborating with various teams across the company. Your influence will directly impact data-driven business decisions and foster a culture of creativity and innovation within your team. You'll stay ahead of industry trends, applying cutting-edge techniques to solve complex challenges, and ensuring Visa remains a leader in the data space. This hybrid role allows flexibility in how you approach your work, fostering an engaging environment where new ideas and continual learning thrive. If you're excited about data's potential to create business opportunities and keen to shape the future of data usage at Visa, come join us in this rewarding journey toward transformation!

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

What responsibilities does the Director of Internal AI & Data Science at Visa have?

The Director of Internal AI & Data Science at Visa is responsible for leading a talented team of data scientists to develop AI-driven products, enrich internal data sets, and integrate external data sources. Key responsibilities include overseeing the design and development of large-scale data systems, applying advanced data science techniques, and influencing business decisions through data insights.