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Senior Staff Data Scientist - Director level - job 17 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
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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 Senior Staff Data Scientist - Director level, Visa

We are excited to announce an opening for a Senior Staff Data Scientist at Visa in Austin, where your expertise will play a pivotal role in shaping our data strategies. In this dynamic position, you’ll build on our existing data capabilities by collecting and analyzing diverse datasets to drive meaningful insights and deliver cutting-edge machine learning and AI solutions. You’ll be instrumental in empowering teams across the organization to use data for smarter decision-making, operational excellence, and innovative problem-solving. If you’re a seasoned professional with a knack for data strategy and governance, this position offers a unique opportunity to make significant contributions to Visa’s vision as a leader in the data-driven industry. This is a hands-on role, ideal for self-starters who are adaptable to a fast-paced and startup-like atmosphere. Your responsibilities will include collaborating with product and engineering teams, experimenting with various data sets, and developing predictive models that align with business needs. We value individuals who pay close attention to detail and can work effectively both independently and in cross-functional teams. Get ready to craft data transformations, build custom algorithms, and provide impactful analytic solutions that will drive our organization forward. This hybrid position allows you to blend remote work with in-office collaboration, and we expect our hybrid employees to spend about 50% of their time in the office. If you’re ready to leverage your skills in a role where you can truly make a difference, we’d love to hear from you!

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

As a Senior Staff Data Scientist at Visa, your main responsibilities will include formulating business problems as technical data challenges, collaborating with product and engineering teams on solutions, and delivering prototypes based on real-time needs. You will also experiment with data sets, build necessary transformations on both structured and unstructured data, and design algorithms that meet our business objectives.

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What qualifications do I need to apply for the Senior Staff Data Scientist position at Visa?

To apply for the Senior Staff Data Scientist position at Visa, you should have a strong academic background, deep expertise in data strategy and analytics, and excellent software engineering skills. We seek professionals who are self-starters comfortable navigating ambiguity and have a strong attention to detail, with the ability to collaborate effectively across teams.

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What kind of work environment can I expect as a Senior Staff Data Scientist at Visa?

The work environment for a Senior Staff Data Scientist at Visa is a hybrid setup that allows you to balance remote and in-office work. We promote a flexible and collaborative atmosphere where you'll engage with cross-functional teams to create impactful data-driven solutions while being part of an innovative culture.

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How does a Senior Staff Data Scientist contribute to Visa’s strategic vision?

As a Senior Staff Data Scientist, your contributions directly enhance Visa's strategic vision by leveraging data to identify patterns, trends, and correlations within payment data. Your insights will help drive decision-making, operational improvements, and innovative solutions that shape the future of Visa as a leading data-driven organization.

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What tools and techniques does a Senior Staff Data Scientist at Visa use?

In this role, you will utilize a variety of tools and techniques including machine learning algorithms, statistical analysis methods, data visualization software, and custom solutions tailored to specific business requirements. Your familiarity with both in-house and third-party data sets will be essential for driving insights and delivering analytics solutions.

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Common Interview Questions for Senior Staff Data Scientist - Director level
Can you describe your experience with machine learning and how it relates to the Senior Staff Data Scientist role?

When answering this question, highlight specific machine learning projects you've worked on, the algorithms used, and the impact your work had on business decisions. Discuss your hands-on experience as well as how you have collaborated with teams to implement machine learning solutions effectively.

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How do you handle ambiguity in data projects, particularly as a Senior Staff Data Scientist?

Demonstrate your problem-solving approach by mentioning a particular instance where you faced uncertain data challenges. Talk about your methods for clarifying objectives, gathering key insights, and formulating clear strategies from ambiguous data situations.

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What techniques do you use for data transformation and why are they important?

Outline specific data transformation techniques you use, such as normalization, aggregation, or pivoting. Explain the importance of these transformations in preparing data for analysis and modeling, and share examples of how they have led to more effective outcomes in past projects.

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Describe a time you worked collaboratively with product and engineering teams.

Use the STAR method (Situation, Task, Action, Result) to structure your response. Describe a collaborative project, your role in bridging the teams, the challenges you faced, and the ultimate success that came from effective teamwork.

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What methods do you implement to monitor model performance in production?

Discuss the techniques you deploy for tracking and ensuring model performance, such as A/B testing, regular performance checks, and feedback loops. Provide examples of how you’ve utilized these methods to improve model efficacy and adapt to changes.

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How do you approach developing a predictive pipeline?

Explain your processes for constructing a predictive pipeline from data extraction through feature engineering and model deployment. Emphasize the importance of automation and efficiency, as well as how you ensure the pipeline meets business needs.

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What is your experience with both structured and unstructured data?

Share your familiarity with various data types and the different techniques you apply to analyze each. Provide examples from your experience that demonstrate your adaptability and success in deriving insights from both structured and unstructured datasets.

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

Show your commitment to continuous learning by discussing the resources you utilize, such as online courses, publications, and conferences, and how you've applied new trends or tools in your professional work.

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Can you provide an example of a data-driven decision that influenced business strategy?

Here, you should detail a specific scenario where your insights led to a significant business decision. Focus on the data used, interpretation, and how the outcome positively impacted the organization.

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What are the biggest challenges you foresee in the role of a Senior Staff Data Scientist at Visa?

Discuss potential challenges like data governance, data quality, or aligning analytics with business needs, and describe how your skills will effectively tackle these challenges to drive success in the role.

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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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