Principal Data Scientist at Authorize.net (Visa) - job 2 of 20

As a Principal Data Scientist at Authorize.net, you'll play a crucial role in shaping the direction of data science initiatives aligned with Visa’s technology goals. Your responsibilities will include leading the use of Generative AI to streamline business workflows and improve efficiency in dispute management. You'll build high-fidelity risk assessment models and engineering systems to run them at scale while maintaining data quality through rigorous governance and processing principles.

To thrive as a Principal Data Scientist at Authorize.net, you should have a robust background in machine learning and applied science, especially within the fintech domain. A Master's or Ph.D. in a relevant field is typically preferred, along with experience in developing predictive models and managing complex data workflows. Proficiency in data wrangling, data modeling, and utilizing artificial intelligence in practical applications is essential for success in this role.

The Principal Data Scientist position at Authorize.net follows a hybrid work model where employees alternate time between remote work and in-office presence. You can expect to work from the office 2-3 set days a week, based on business needs, with the intention of balancing the flexibility of remote work with the collaborative aspects of being physically present with your team. This approach fosters a productive working environment while allowing for work-life balance.

In the role of Principal Data Scientist at Authorize.net, your impact will be substantial as you collaborate with a team dedicated to revolutionizing payment technology. You will shape the development of innovative tools and processes that enhance data management while improving transaction security. Your expertise in AI and data science will empower businesses to efficiently manage transactions and risk, ultimately transforming the financial landscape for millions worldwide.

Principal Data Scientists at Authorize.net utilize a range of advanced technologies including machine learning algorithms, Generative AI, and big data platforms. You will leverage tools and programming languages such as Python or R, alongside SQL for data manipulation, and various data processing frameworks to build and deploy models at scale. Staying updated on cutting-edge data technologies is crucial for excelling in this role and effectively meeting today’s data challenges.

When responding to this question, focus on specific projects you've worked on, highlighting the machine learning models you developed and the impact they had on business processes. Mention any challenges you faced and how you overcame them while ensuring data quality and adherence to governance principles.

To answer this, discuss methodologies such as data validation, testing protocols, and data governance practices you implement in your work as a Principal Data Scientist. Highlight your experience in data wrangling and utilizing AI for maintaining data integrity through complex data pipelines.

When answering, detail your collaborative experiences, emphasizing your communication and leadership skills. Provide examples of how you have worked with engineers and data scientists to overcome obstacles or achieve project deadlines, especially in high-stakes environments like fintech.

In answering this question, recall a specific accomplishment that had a measurable impact, whether through improved efficiencies, risk assessments, or innovative solutions you implemented. Use quantitative metrics to underscore your success and relevance to the Principal Data Scientist role at Authorize.net.

Discuss the resources you utilize such as online courses, webinars, professional networks, and research publications. Emphasize your commitment to lifelong learning and how you apply new knowledge to enhance your projects and innovations in the field.

Outline your approach to diagnosing issues with live models, detailing the systematic steps you took to analyze performance and identify the root cause of the problem. Discuss any collaborative efforts with production support teams to rectify the issue and ensure consistent service.

When addressing this question, elaborate on specific use cases you've encountered where Generative AI enhanced workflows, particularly in dispute management or automating data processes. Explain how you measure success when implementing AI techniques into your projects.

Provide examples of how you have simplified data insights into actionable recommendations for stakeholders. Discuss techniques you use such as data visualization tools and clear storytelling to convey critical information without overwhelming your audience.

Discuss the volume, variety, and velocity of data challenges you've encountered. Detail how you handled these issues through effective data management practices, tools, or architectures that helped you to maintain data quality and consistency.

Articulate your enthusiasm for joining Authorize.net, emphasizing how their vision aligns with your professional values and goals. Discuss your interests in the fintech space and how you can contribute to their mission of innovating payment technologies and solutions.