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Director, Internal AI & Data Science - job 31 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

$150000 / YEARLY (est.)

min

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$120000K

$180000K

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

At Visa, we're seeking a dynamic Director of Internal AI & Data Science to join our team in Atlanta. This is an exciting opportunity where your passion for data can truly make a difference! With the ever-evolving role of data in shaping our future, you'll play a significant part in unlocking its vast potential for businesses, consumers, and communities worldwide. As part of the Global Data Office, you will lead a talented team of data scientists in developing sophisticated AI-driven products and services aimed at integrating various data sources. Your leadership will be crucial in designing large-scale data science systems and fostering a culture of innovation and collaboration within your team. You'll oversee the collection and processing of external structured and unstructured data and utilize advanced modeling techniques to create insights that enhance Visa’s understanding of payment technologies. Staying updated with the latest trends in AI and machine learning, you'll apply your expertise in multiple programming languages, ensuring our data science capabilities align with business objectives. Communication is key in this role, and you'll be responsible for translating complex technical concepts into actionable insights for senior leadership and business partners. Join us at Visa and be a part of a team that's dedicated to ensuring the responsible use of data while driving impactful change in the world of payments. Embrace the opportunity to lead a passionate team, innovate, and transform data into valuable business insights.

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

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

The Director of Internal AI & Data Science at Visa is responsible for overseeing the design, development, and delivery of processes for collecting and integrating data. This includes overseeing the transformation of data into intelligent personas and tags, leading a team of data scientists, and applying advanced data techniques to drive business impact. Collaboration with cross-functional teams and communicating complex data insights to stakeholders are also crucial aspects of this role.