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Senior Staff Data Scientist - Director level - job 12 of 20

The Senior Staff Data Scientist, you will play a crucial role in building our data capabilities, collecting, analyzing, driving insights, and delivering machine learning and AI solutions that enhance our offerings. Your will play a pivotal role in building the organization’s “data muscle”, empowering teams to leverage data for smarter decisions, operational excellence and innovation. This is a unique opportunity to work in a fast-paced and startup environment where your contributions will have a direct impact.

This role represents an exciting opportunity to make key contributions to Visa's strategic vision as a world-leading data-driven company. The role requires a seasoned professional with deep expertise in data strategy, analytics, governance paired with a hands-on and scrappy mindset to deliver impactful results. The successful candidate must have strong academic track record and demonstrate excellent software engineering skills. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills. 

To be successful in this position, you must be highly effective working both independently and in cross-functional capacities.

 

Essential Functions

  • Formulate business problems as technical data problems while ensuring key business drivers are collected in collaboration product stakeholders.
  • Work with product and engineering to ensure effective solutions. Deliver prototypes and production code based on need.
  • Experiment with in-house and third-party data sets to test hypotheses on relevance and value of data to business problems.
  • Build needed data transformations on structured and un-structured data.
  • Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, analytics, and statistical techniques.
  • Devise and implement methods for efficiently monitoring model efficiency and performance in production.
  • Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.
  • Contribute to development and adoption of shared predictive analytics infrastructure.
  • Data mining, processing and analyzing large datasets to generate insightful reports.
  • Develop data modeling processes and algorithms to derive meaningful actionable insights from structured and unstructured big data
  • Utilize statistical analysis, data visualization, and machine learning techniques to extract meaningful insights from datasets. Identify and interpret patterns, trends, and correlations within payment data.
  • Generate comprehensive dashboards and reports for organizational leadership to use in a business setting.

 

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
max
$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 Senior Staff Data Scientist - Director level, Visa

As a Senior Staff Data Scientist at Visa in Austin, you'll be at the forefront of driving data capabilities that fuse innovative ideas with advanced analytics. Imagine a role where you can influence how data shapes the company's future, utilizing your expertise in machine learning and AI to deliver tangible solutions. This is not just about crunching numbers; it's about empowering teams to make smarter, data-driven decisions that will lead to operational excellence and innovative solutions. Your scrappy mindset will be crucial as you formulate complex business problems into manageable technical data challenges, collaborating with product and engineering teams to create effective solutions. You'll be experimenting with both in-house and third-party datasets, building powerful algorithms, and transforming unstructured data into actionable insights. As you dive deep into mining, processing, and analyzing large datasets, you'll generate comprehensive reports and engaging dashboards that provide leadership with the insights they need to drive strategic decisions. By taking ownership of the predictive analytics infrastructure, you'll automate processes to ensure maximum efficiency and productivity. Joining Visa means contributing to a data-driven culture in a fast-paced, startup-like environment where your expertise aims to make a real impact. If you're ready to roll up your sleeves and take data science to the next level, we would love to hear from you!

Frequently Asked Questions (FAQs) for Senior Staff Data Scientist - Director level Role at Visa
What are the primary responsibilities of a Senior Staff Data Scientist at Visa?

The primary responsibilities of a Senior Staff Data Scientist at Visa include formulating business problems into technical data challenges, collaborating with product stakeholders, and developing prototypes and production code. You'll experiment with various data sets, build and refine algorithms, and create methods for monitoring model performance. Additionally, producing insightful reports and comprehensive dashboards for organizational leadership is a major part of the role.

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What qualifications should a candidate have for the Senior Staff Data Scientist position at Visa?

A successful candidate for the Senior Staff Data Scientist role at Visa should hold a strong academic track record in data science, analytics, or related fields. It is essential to have extensive expertise in data strategy, analytics, and governance, combined with excellent software engineering skills. Strong attention to detail and the ability to work collaboratively in cross-functional teams are also critical.

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What technical skills are necessary for a Senior Staff Data Scientist at Visa?

Technical skills necessary for a Senior Staff Data Scientist at Visa include proficiency in machine learning and statistical analysis, data visualization, and programming languages such as Python or R. Familiarity with big data processing tools and frameworks is crucial for handling and analyzing large datasets effectively.

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How does the Senior Staff Data Scientist contribute to Visa's data vision?

The Senior Staff Data Scientist at Visa plays a key role in enhancing the organization's data capabilities by leveraging analytical skills to drive insights that inform strategic decisions. This position entails building the company's 'data muscle,' fostering a culture of data-driven innovation, and ensuring that data analytics align with business goals.

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What is the working environment for the Senior Staff Data Scientist position at Visa?

The working environment for the Senior Staff Data Scientist at Visa is hybrid, allowing employees to alternate between remote and office work. Employees in hybrid roles are expected to work in the office 2-3 days a week, enhancing collaboration while offering flexibility to balance personal and professional commitments.

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Common Interview Questions for Senior Staff Data Scientist - Director level
What methodologies do you use to analyze and interpret data?

When answering this question, emphasize your familiarity with various methodologies such as statistical analysis, machine learning, and data mining. Discuss specific tools and techniques you’ve utilized, and illustrate how you apply these methodologies to derive actionable insights from large data sets.

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Can you describe a specific project where you built a predictive model?

In your response, detail a specific project, outlining the problem you aimed to solve, the data you used, the model you built, and the outcomes it achieved. Be sure to highlight the iterative process you followed and any collaboration with other teams.

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How do you ensure the quality and integrity of data used in your models?

It's essential to discuss your approaches to data validation and cleaning processes. Mention any specific tools or techniques you deploy to check for inconsistencies and ensure that the data used is both reliable and valid before proceeding with analysis.

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How do you approach collaboration with cross-functional teams?

Highlight your communication skills and the importance of understanding different perspectives. Explain how you’ve collaborated with product managers, engineers, and other stakeholders in past roles to ensure alignment on objectives and successful project outcomes.

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What tools and technologies do you prefer for data visualization?

Discuss your favored tools for data visualization, such as Tableau, Power BI, or Python libraries like Matplotlib and Seaborn. Explain why you prefer these tools and include examples of how you’ve used them to effectively present data insights.

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Describe how you handle ambiguity in data projects.

Address how you thrive in situations where not all data is available or where requirements are not fully defined. Detail your strategies for clarifying needs, gathering more information, and maintaining flexibility in your approach to find solutions.

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How do you prioritize tasks when managing multiple data projects?

Explain your time management techniques and how you assess project priorities based on business impact, deadlines, and resource availability. Mention any tools you use for project management or tracking progress.

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What is your experience with machine learning algorithms?

Provide insights into the algorithms you’ve utilized, such as linear regression, decision trees, or neural networks. Include examples where you successfully implemented these algorithms to tackle specific data problems and discuss the outcomes.

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How do you keep up with trends in data science and analytics?

Share the resources you utilize to stay updated, such as attending conferences, following thought leaders in data science on social media, or engaging in online courses. This shows your dedication to continuous learning in the field.

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What role do you see data science playing in a company's overall strategy?

Discuss the substantial impact of data science on business strategy, including how organizations can leverage insights to improve decision-making, drive efficiency, and foster innovation. Illustrate your points with real examples from your experiences.

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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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