Company:
Visa
Location: Miami
Closing Date: 18/10/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Job Description
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 Innovation team under the Global Data Office is creating the next generation of scalable and responsible AI, ML and Data Innovations and products to solve client and consumer problems. We are a cross-functional team of data scientists, product managers, AI and data engineers, program managers focused on generating value for the payments ecosystem. We are dreaming of the next generation of AI features and products.
This position is in the Data Science vertical under the Global AI and Data Innovation team. 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 signals to deliver personalized customer experiences. These personalization models and signals will power Data Tokens and many other personalization-related use cases. The ultimate goal is to better link consumers with products and services, with benefits for every party in the payments ecosystem (consumers, businesses).
Responsibilities include:
Overall design, development and delivery of personalization models and signals to fuel AI products and services on a global scale
Technical Leadership:
Develop and execute a vision for data science capabilities in the personalization space
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 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 personalization data science strategy 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. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
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 Innovation team under the Global Data Office is creating the next generation of scalable and responsible AI, ML and Data Innovations and products to solve client and consumer problems. We are a cross-functional team of data scientists, product managers, AI and data engineers, program managers focused on generating value for the payments ecosystem. We are dreaming of the next generation of AI features and products.
This position is in the Data Science vertical under the Global AI and Data Innovation team. 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 signals to deliver personalized customer experiences. These personalization models and signals will power Data Tokens and many other personalization-related use cases. The ultimate goal is to better link consumers with products and services, with benefits for every party in the payments ecosystem (consumers, businesses).
Responsibilities include:
Overall design, development and delivery of personalization models and signals to fuel AI products and services on a global scale
Technical Leadership:
Develop and execute a vision for data science capabilities in the personalization space
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 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 personalization data science strategy 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. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
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