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Senior Staff Data Scientist - Director level - job 15 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 our vibrant Austin office, you will be at the forefront of transforming how we leverage data across our operations. Your role is crucial as you not only collect and analyze vast datasets but also drive insights that will help shape our machine learning and AI initiatives, enhancing our offerings in a rapidly evolving landscape. Your expertise will be instrumental in building our organization’s 'data muscle,' enabling various teams to make smarter, data-driven decisions while fostering a culture of operational excellence and innovation. In this dynamic startup-like environment, your contributions will directly impact our strategic vision as a leader in data-driven solutions. We’re looking for someone with a solid academic background and exceptional software engineering skills, ready to tackle ambiguity with creativity and precision. You'll collaborate closely with product stakeholders to translate business problems into technical data challenges, ensuring we deliver effective, production-ready solutions. By experimenting with diverse datasets and developing unique modeling algorithms, you will help us unlock actionable insights from both structured and unstructured data. Additionally, you will implement methods for monitoring model efficiency and automate the predictive pipeline, significantly enhancing our analytics infrastructure. If you are a self-starter, a collaborative communicator, and eager to make a mark in the data science realm, this is the opportunity for 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 your company?

As a Senior Staff Data Scientist, key responsibilities include formulating business problems into technical data challenges, collaborating with engineering teams to develop prototypes, experimenting with various data sets, and creating custom algorithms for machine learning and analytics. You’ll also be responsible for data mining, processing large datasets, and generating comprehensive reports for organizational leadership.

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What qualifications are needed for a Senior Staff Data Scientist position?

To qualify for the Senior Staff Data Scientist role, candidates should have a strong academic track record and demonstrated expertise in data strategy, analytics, and software engineering. Additionally, familiarity with machine learning techniques and the ability to work independently and collaboratively in cross-functional teams is essential.

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How does the Senior Staff Data Scientist contribute to the company’s strategic vision?

The Senior Staff Data Scientist plays a vital role in our strategic vision by enabling data-driven decision-making throughout the organization. By developing advanced data modeling processes and generating actionable insights from big data, you'll help drive innovation and operational excellence, positioning our company as a leader in the industry.

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What is the work environment like for the Senior Staff Data Scientist role?

The work environment for the Senior Staff Data Scientist role is hybrid, allowing for flexibility between remote and onsite work. Employees can expect to collaborate in the office 2-3 days a week while also having the ability to work remotely, which promotes a balanced work-life dynamic in a fast-paced, innovative setting.

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What skills are most important for success as a Senior Staff Data Scientist?

Successful candidates for the Senior Staff Data Scientist role must possess strong analytical and problem-solving skills. Additionally, being detail-oriented, having excellent collaboration abilities, and being comfortable with ambiguity are crucial for navigating the complexities of data strategy and driving impactful results.

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Common Interview Questions for Senior Staff Data Scientist - Director level
Can you explain a challenging data problem you have solved in the past?

When responding, highlight a specific challenge, your approach to breaking it down into manageable parts, the analytical tools you used, and the outcomes. Emphasize your thought process and collaboration with stakeholders to ensure alignment with business goals.

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Describe your experience with machine learning algorithms and their application.

Discuss the machine learning algorithms you are comfortable with, providing examples of projects where you applied them. Highlight the impact these algorithms had on achieving specific business outcomes, demonstrating your expertise in practical applications.

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How do you ensure the quality of your data analysis work?

Explain your approach to data validation, cleaning, and the techniques you use to monitor model performance. Stress the importance of thorough testing and iteration to ensure the reliability and relevance of your insights.

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What steps do you take to convert business problems into data challenges?

Outline your process of collaborating with product stakeholders, discussing how you identify key business drivers and translate them into technical requirements. Provide an example of a successful project where you effectively bridged the gap between business and data.

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How do you keep up with advancements in data science and machine learning?

Mention specific resources, such as online courses, conferences, and research papers, that you follow to stay informed about industry trends. Emphasize your commitment to continuous learning and professional development to remain at the forefront of the field.

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What approach do you take to visualizing data insights for stakeholders?

Discuss the tools and techniques you use for data visualization, focusing on how you tailor your visualizations to suit different audiences. Provide an example where your visual insights led to important business decisions.

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Explain a time when you had to work cross-functionally with different teams.

Share a specific instance where effective communication and collaboration with cross-functional teams led to project success. Highlight any challenges you faced and how you addressed them to foster a teamwork-driven environment.

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How do you handle conflicting priorities and tight deadlines?

Provide an example of a situation where you successfully managed multiple projects. Discuss your prioritization strategies and how you communicated with stakeholders to manage expectations while delivering quality results.

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What methods do you utilize for monitoring and automating the predictive pipeline?

Discuss technologies and tools you're experienced in that facilitate monitoring and automation of predictive analytics. Share how these methods enhance efficiency and accuracy in data analysis.

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Tell us about a successful project where you derived actionable insights from large datasets.

Share the project outline, focusing on the methods you applied to extract insights from big data and the impact these insights had on business decisions. Highlight any innovative techniques you implemented during the project.

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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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