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Principal Data Scientist at Authorize.net (Visa) - job 19 of 20

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

$150000 / YEARLY (est.)
min
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$120000K
$180000K

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

At Authorize.net (Visa), we're on the lookout for a Principal Data Scientist to come aboard in our vibrant Bellevue office. As part of Visa's Technology Organization, you're not only joining a community of innovators but also a powerhouse that processes more than 65,000 secure transactions per second worldwide! Your role will be central to shaping the future of commerce through data solutions and machine learning advancements. In this position, you'll leverage your expertise in generative AI to enhance workflows critical to our mission, while also developing high-fidelity models for effective risk assessment in the fintech space. Collaborating with our passionate team, you'll tackle complex challenges that impact millions daily, ensuring we deliver high-quality data management across various platforms. Your insights will help reshape how we develop data products, driving efficiencies through advanced automation and data extraction techniques. Moreover, this hybrid role gives you flexibility, balancing the dynamic energy of office collaboration with the comfort of remote work. Are you ready to make a lasting impact and be at the forefront of changing the way data is handled in the payments industry? Let’s create something extraordinary together!

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?

As a Principal Data Scientist at Authorize.net, your primary responsibilities will include utilizing machine learning techniques to improve core business workflows, particularly in dispute management and merchant representment. You will develop high-fidelity models for risk assessment and build engineering systems that maintain these models in production workflows. Additionally, oversight of data quality processes and alignment with data management principles will be crucial to ensure the integrity of our data products.

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What qualifications are needed for the Principal Data Scientist position at Authorize.net?

To become a Principal Data Scientist at Authorize.net, candidates should have extensive experience in data science, machine learning, and fintech applications. A strong academic background in computer science, statistics, or related fields is essential. Proficiency in programming languages such as Python or R along with experience in data wrangling, modeling, and applying generative AI methodologies is also required. Strong leadership and communication skills will help facilitate collaboration across multiple functions.

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How does the Principal Data Scientist at Authorize.net contribute to business efficiency?

In the role of Principal Data Scientist at Authorize.net, you will drive business efficiency by automating data processing workflows and implementing advanced data protocols. By developing innovative machine learning models and optimizing data extraction techniques, you'll ensure timely access to high-quality data, which in turn aids in informed business decision-making and improves overall operational efficiencies.

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Is the Principal Data Scientist role at Authorize.net a hybrid position?

Yes, the Principal Data Scientist position at Authorize.net is a hybrid role. Employees are expected to work from the office 2-3 set days a week, allowing for flexibility to alternate between remote and office work based on business needs. This format encourages collaboration while accommodating the changing dynamics of today's work environment.

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What impact does a Principal Data Scientist have on products at Authorize.net?

As a Principal Data Scientist at Authorize.net, the impact on products is substantial. You will lead the development of innovative data-driven solutions and machine learning applications that address complex challenges in the payments industry. By shaping the tools and processes that govern data management, you'll ensure that our products are not only effective but also secure and scalable, ultimately enhancing the experience for millions of users worldwide.

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Common Interview Questions for Principal Data Scientist at Authorize.net (Visa)
Can you explain a complex data model you've built in the past?

It’s important to be specific about the context of the project and the problem your model aimed to solve. Discuss how you approached the data collection, preprocessing, and analysis aspects, and highlight the decisions that led to the final model. Include both the technical aspects and the impact it had on the business outcomes.

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How do you ensure the quality of data in your projects?

Discuss your understanding of data management principles and how you implement validation checks throughout the data pipeline. Highlight techniques you use, such as data wrangling and transformation processes, to maintain high data quality, completeness, and consistency.

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What methods do you use for risk assessment in fintech?

Be prepared to describe different risk assessment methodologies, such as predictive modeling and machine learning approaches that you have applied. Explain how these methodologies can identify potential risks in transactions or business operations and discuss your use of data to support your findings.

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How do you incorporate machine learning into your data projects?

Detail your experience with machine learning frameworks and algorithms. Discuss how you identify suitable machine learning applications for specific problems and elaborately describe any projects where you designed, tested, and deployed machine learning models.

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Describe a time you led a team through a challenging project.

Use the STAR method (Situation, Task, Action, Result) to explain a specific project. Focus on your leadership style, how you managed team dynamics, and the strategies you implemented to overcome challenges and achieve the project goals.

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What strategies do you use for data visualization?

Discuss tools and techniques you are adept with, such as Tableau or Python libraries. Highlight how you tailor visualizations for different audiences and ensure that key insights are communicated effectively.

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How do you keep abreast of new technologies in data science?

Share your strategies for continuous learning, such as following industry blogs, participating in workshops, or engaging with professional communities. Mention any specific technologies or methodologies you are currently exploring.

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How do you collaborate with cross-functional teams at work?

Highlight your communication skills and the importance of understanding different perspectives. Discuss methods you employ to facilitate cooperation, such as regular meetings, shared documentation, and fostering an inclusive environment for brainstorming.

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What do you believe is the future of data science in fintech?

Share your insights on emerging trends such as AI advancements, the role of big data, and regulatory considerations. Discuss how these trends can shape the industry and what steps you believe organizations should take to adapt.

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Can you provide an example of how you improved a workflow with your data science skills?

Describe a specific scenario where you identified bottlenecks in a workflow and used your data analysis skills to propose or implement a solution. Focus on the methods used, tools applied, and the resulting improvements in efficiency or effectiveness.

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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 2, 2025

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