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Principal Data Scientist at Authorize.net (Visa) - job 9 of 21

Visa’s Technology Organization is a community of problem solvers and innovators reshaping the future of commerce. We operate the world’s most sophisticated processing networks capable of handling more than 65k secure transactions a second across 80M merchants, 15k Financial Institutions, and billions of everyday people. While working with us you’ll get to work on complex distributed systems and tackle massive scale problems centered on new payment flows, business and data solutions, cyber security, and B2C platforms.

 

The Opportunity:

We are seeking a versatile, curious, and energetic Senior Director to join our team of passionate and dedicated engineers and data scientists. We collaborate on Data Engineering and Machine Learning developments at Visa, tackling complex challenges on a global scale! As a Senior Director at Visa, you will play an integral role in a multi-functional development team, inventing, designing, building, and testing products that serve a truly global customer base. Join us and see how your efforts will shape the digital future of payments.

You will have an opportunity to changing the way data products are developed at Visa!

 

Essential Functions:

  • Be a technology thought leader in the domain of ML and applied science in fintech space.

  • Use Generative AI to improve business workflows around core mission critical logic related to dispute management and merchant representment.

  • Build metrics and evaluations as we migrate business logic to LLMs.

  • Build high fidelity models for risk assessment in fintech space

  • Build engg systems to run the models at scale in production workflows.

  • Ensures alignment to data management principles, governance, process, and tools to maintain quality across all projects.

  • Supervises testing code in a common testing environment to assess compatibility.

  • Leads regular calls with production support teams to address issues with code.

  • Shapes the direction for the development of tools and automation processes that assist in transforming, optimizing, managing, accessing, deploying, and monitoring data processes in batches and in real time.

  • Monitors and supervises efforts to automate advanced data protocols, reduction techniques, and aggregation approaches to validate the quality of extracted data across the data pipeline.

  • Leads efforts to drive efficiencies across data extraction and ensures data quality and completeness using data wrangling, complex data modeling, and artificial intelligence.

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.

Average salary estimate

$175000 / YEARLY (est.)
min
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$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 Principal Data Scientist at Authorize.net (Visa), Visa

If you're eager to make a significant impact in the fintech industry, the Principal Data Scientist position at Authorize.net (Visa) in Bellevue could be your next big step! At Visa's Technology Organization, we are a vibrant community of innovators and problem solvers dedicated to reshaping the future of commerce. In this role, you'll engage with the world's most sophisticated processing networks, tackling massive scale challenges involving new payment flows, data solutions, and advanced cyber security measures. As a Principal Data Scientist, you'll be a key player, leading cutting-edge developments in Machine Learning and Data Engineering, while working alongside a talented group of engineers and data scientists who are as passionate about technology as you are. Your expertise in generative AI will play a critical role in transforming business workflows, particularly in dispute management. You'll also focus on creating high-fidelity risk assessment models and engineering systems that ensure smooth production workflows. With a commitment to data integrity, you will champion best practices in data management and governance, oversee critical testing procedures, and spearhead the automation of advanced data protocols. Your leadership will shape tools that enhance data extraction and monitoring processes. This hybrid position offers flexibility, allowing you to blend remote work with in-office collaboration several days a week. So, if you're ready to help redefine how data products are developed at Visa, join us and contribute to the digital future of payments!

Frequently Asked Questions (FAQs) for Principal Data Scientist at Authorize.net (Visa) Role at Visa
What are the main responsibilities of a Principal Data Scientist at Authorize.net (Visa)?

As a Principal Data Scientist at Authorize.net (Visa), your primary responsibilities include leading Machine Learning and Data Engineering projects, building advanced risk assessment models, and utilizing Generative AI to enhance core business workflows. You will oversee data management principles, innovate testing procedures, and ensure data quality throughout various projects. Your role is pivotal in shaping the future of data products at Visa.

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What qualifications do I need to apply for the Principal Data Scientist position at Authorize.net (Visa)?

To apply for the Principal Data Scientist role at Authorize.net (Visa), you should have a strong background in data science and machine learning, typically evidenced by a master's or doctoral degree in a related field. Experience in fintech, particularly with data management and advanced analytics, is crucial. Proficient knowledge of Generative AI and solid programming skills to build and evaluate models at scale are also highly valued.

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How does the Principal Data Scientist at Authorize.net (Visa) use Generative AI?

In the role of Principal Data Scientist at Authorize.net (Visa), Generative AI is leveraged to improve business workflows, specifically in critical areas such as dispute management and merchant representment. By integrating generative AI into these processes, you can streamline operations and enhance the overall efficiency and effectiveness of data-driven solutions within the organization.

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What is the work environment like for the Principal Data Scientist position at Authorize.net (Visa)?

The work environment for the Principal Data Scientist at Authorize.net (Visa) is dynamic and collaborative, set within a hybrid model. This allows you the flexibility to work both remotely and in the office, striking a balance that fosters teamwork and innovation. You'll engage regularly with multi-functional teams, cultivating a culture of problem-solving and data excellence.

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What are the growth opportunities for a Principal Data Scientist at Authorize.net (Visa)?

As a Principal Data Scientist at Authorize.net (Visa), you will have significant growth opportunities. The role places you at the forefront of innovation in fintech, allowing you to influence developments in data science and machine learning. Your contributions can lead to the advancement of technology and potentially open pathways for senior leadership roles within Visa's expansive global organization.

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Common Interview Questions for Principal Data Scientist at Authorize.net (Visa)
What experience do you have with Machine Learning in previous roles?

In answering this question, outline your specific experiences with Machine Learning, highlighting projects that showcase your skills in developing models and algorithms. Discuss any tools or programming languages you utilized, and be sure to mention how your contributions led to tangible improvements in business outcomes.

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How do you approach building high-fidelity risk assessment models?

When asked about building risk assessment models, share your methodology. Discuss your approach to data selection, model training, validation, and deployment. Highlight any relevant tools or frameworks you've used, and emphasize the impact your models had on risk management and decision-making processes.

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Can you explain a time when you improved a business workflow using data science?

For this question, narrate a specific instance where your data science techniques led to the optimization of a business workflow. Detail the challenges faced, the strategies implemented, and the resulting improvements. Show how your analytical skills directly benefited the organization.

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What are the latest trends in data science that you believe are relevant to fintech?

In responding, discuss current trends such as the integration of Generative AI, advancements in predictive analytics, or the shift towards real-time data processing. Connect these trends to how they could be utilized within the fintech sector, particularly in enhancing payment systems or customer experiences.

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Describe your experience with data management and governance.

When discussing your experience with data management and governance, provide examples where you ensured data quality and compliance with best practices. Share any specific frameworks or tools you've used to maintain data integrity during projects, and discuss how this contributed to successful outcomes.

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How do you validate and test your models?

In your response, describe the validation techniques you employ, such as cross-validation, and discuss your testing methods for ensuring accuracy and reliability. Mention any metrics you use to assess model performance and how you iterate based on results.

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How do you handle communication and collaboration with cross-functional teams?

Highlight your approach to communication and collaboration, discussing specific tools or methods that facilitate teamwork. Emphasize your ability to bridge gaps between technical and non-technical stakeholders, ensuring that everyone is aligned on goals and project outcomes.

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What is your experience with deploying models in production?

Discuss your experience in deploying models, focusing on the tools and processes you used. Talk about any challenges you encountered during deployment and how you overcame them to ensure the models operated smoothly in a production environment.

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What motivates you to stay updated with advancements in data science?

Share your passion for data science and your commitment to continuous learning. You might mention following industry leaders, participating in workshops, or engaging in online courses that keep your skills sharp and allow you to apply the latest techniques in your work.

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How would you handle a situation where a project did not go as planned?

When addressing this question, outline your problem-solving approach. Discuss how you assess the situation, gather feedback, and implement adjustments to get the project back on track. Emphasize the importance of learning from experiences to improve future project management.

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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 3, 2025

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