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Sr. Data Scientist, Risk and Identity Solutions

Job Description

We are currently seeking a senior data scientist to drive analytical projects and insights for Visa Predictive Modeling team based at Visa's office in Atlanta, GA.


The predictive modeling team within Visa Value-Added Services is responsible for building and maintaining major consumer behavior models to solve business problem for clients and issuers. The team closely collaborates with other analytic stakeholders to understand the business problem in order to determine the most appropriate analytic approach that provides meaningful results to customers. Responsibilities include delivering projects on time and within scope with an in-depth knowledge of big data and cutting-edge data mining techniques as well as the use of predictive, classification, machine learning and alternate analytic algorithms for modeling and segmentation.

Essential Functions

  • Validate newly developed risk models, generate performance analysis at both aggregate and issuer levels, and interpret and present results to non-technical audiences.
  • Prepare new model testing packages for production deployment, and support model installations and calibration.
  • Drive analytic product development by conducting statistical analyses on various data sources and enhance products through innovative applications of the analysis.
  • Define financial and analytic metrics to measure development and production outcomes and roduce performance reports.
  • Identify opportunities to automate repeatable analyses or build self-service tools for business users.
  • Support sales and marketing efforts with robust statistical and financial analysis, perform ad-hoc analyses to respond to fast-changing market demands.
  • Analyze transaction data using Hadoop/Cloud and big data technologies for internal and external product owners and develop deeper insights into products using advanced statistical methods.
  • Develop and derive transaction attributes to enhance analytic products.
  • Ensure project delivery within timelines and meet critical business needs.
  • Collaborate with cross-functional teams and engage with internal and external stakeholders.
  • Advocate for big data innovations and promote analytic education throughout the organization.

 

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.

Qualifications

Basic Qualifications

  • 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD


Preferred Qualifications

  • 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
  • Graduate degree in a quantitative field such as statistics, mathematics, economics, engineering, or related disciplines.
  • Multiple years of experience in predictive modeling functions preferred.
  • Modeling experience in the bankcard industry or financial services, particularly for fraud, credit risk, bankruptcy, or marketing, is preferred.
  • At least 3 years of experience with big data tools (e.g. Hive, Spark, Scala) and practical experience using Hadoop and related query languages.
  • High proficiency in Python, Spark, and Unix/Linux scripting.
  • Extensive experience with SQL/Hive for data extraction and aggregation.
  • Hands-on experience with deep learning is preferred.
  • Proven team player with strong multi-tasking and problem-solving skills.
  • Demonstrated intellectual and analytical rigor, strong attention to detail, and excellent business writing, verbal communication, and presentation skills.

**No Relocation will be offered for this position -- this is on site role (Hybrid) in our Atlanta Office   

Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer.  Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.  Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is $132,500 to $172,500  per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

Average salary estimate

$152500 / YEARLY (est.)
min
max
$132500K
$172500K

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 Sr. Data Scientist, Risk and Identity Solutions, Visa

At Visa, we're looking for a talented Sr. Data Scientist to join our Risk and Identity Solutions team in Atlanta, GA. If you're passionate about data and have a knack for predictive modeling, you might be the perfect fit for our innovative environment. In this role, you'll drive analytical projects by leveraging your expertise in big data and cutting-edge data mining techniques. Your primary responsibility will involve building and maintaining consumer behavior models that address business challenges for our clients and issuers. You'll collaborate closely with various analytic stakeholders to ensure we're taking the best approach to deliver insights that truly matter. With at least 5 years of relevant experience and a strong foundation in statistical modeling, you’ll have the opportunity to validate risk models, prepare them for production, and devise metrics that measure outcomes effectively. Plus, you'll support sales and marketing with robust analyses while advocating for big data innovations across the organization. This hybrid position allows you to enjoy flexibility between remote work and office days, fostering an environment where you can thrive while contributing to significant business outcomes. If you're ready to elevate your career in a dynamic team at Visa, we’d love to hear from you!

Frequently Asked Questions (FAQs) for Sr. Data Scientist, Risk and Identity Solutions Role at Visa
What are the main responsibilities of a Sr. Data Scientist at Visa?

As a Sr. Data Scientist at Visa, your main responsibilities include delivering analytical projects, building predictive consumer behavior models, validating risk models, and collaborating with cross-functional teams. Additionally, you'll conduct statistical analyses on various data sources, automate repeatable processes, and support sales and marketing initiatives with robust statistical analysis.

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What qualifications do I need to apply for the Sr. Data Scientist position at Visa in Atlanta?

To apply for the Sr. Data Scientist role at Visa, you would typically need at least 5 years of relevant work experience and either a Bachelor's degree or advanced degrees in quantitative fields like statistics or mathematics. Experience with big data tools, predictive modeling, and programming languages like Python is also highly preferred.

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How does Visa approach big data innovations for their Risk and Identity Solutions?

Visa places a strong emphasis on big data innovations within the Risk and Identity Solutions team by leveraging advanced statistical methods, machine learning algorithms, and cloud technologies. As a Sr. Data Scientist, you will advocate for these technologies and enhance analytical products, ensuring we remain at the forefront of data-driven decision-making.

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What kind of projects can I expect to work on as a Sr. Data Scientist at Visa?

In the Sr. Data Scientist role at Visa, you can expect to work on projects that involve modeling consumer behavior, analyzing transaction data, and validating risk models. You’ll also be involved in supporting product development through innovative analytics that address both client and market demands.

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Is the Sr. Data Scientist position at Visa a remote work option?

The Sr. Data Scientist position at Visa offers a hybrid work arrangement, allowing you to alternate between remote work and in-office days. This means you’ll enjoy flexibility while ensuring collaboration with your team and fulfilling business needs.

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Common Interview Questions for Sr. Data Scientist, Risk and Identity Solutions
Can you describe your experience with predictive modeling and how it applies to this Sr. Data Scientist role?

When answering this question, detail your predictive modeling background, emphasizing any relevant projects where you've developed models for risk analysis or consumer behavior. Discuss the tools and techniques you employed, and how your insights contributed to business goals.

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What big data tools are you proficient in, and how have you used them in previous roles?

To effectively answer this question, mention specific big data tools such as Hadoop, Spark, or Hive. Provide examples of how you utilized these tools for data extraction and analysis, and discuss the impact your work had on projects.

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How do you ensure accuracy and validity in the models you develop?

Discuss your approach to model validation, including cross-validation techniques, performance metrics, and how you interpret results. Highlight the importance of iterative testing and refinement to maintain model accuracy.

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Give us an example of how you've collaborated with cross-functional teams in the past.

Focus on a specific instance where your collaboration led to a successful outcome. Describe your role, the teams involved, and the communication strategies you used to align objectives and deliver results.

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What do you consider the most challenging aspect of data science, and how do you overcome it?

Identify a challenge such as data quality issues or staying current with evolving technologies, and describe your strategies to overcome these challenges. Discuss how you continually educate yourself and apply best practices in data handling.

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How would you handle a situation where your analytical results contradicted the business assumptions?

Explain your approach to communicating such results effectively, emphasizing clarity and diplomacy. Discuss how you would present the data and insights, ensuring stakeholders understand the implications while fostering an environment for discussion.

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What experience do you have with machine learning techniques?

Describe any machine learning projects you have undertaken, including algorithms you've implemented and the results obtained. Emphasize your understanding of supervised and unsupervised learning and how these concepts apply to risk and identity solutions.

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Discuss a time when your analysis led to a significant change or decision.

Provide a narrative that showcases your analytical skills, what the analysis was about, and how the findings prompted actionable change. Highlight any positive outcomes for the business as a result.

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What strategies do you use to present complex data insights to non-technical stakeholders?

Talk about techniques such as data visualization, storytelling with data, and focusing on key metrics that align with business goals. Providing examples can help illustrate your effectiveness in communication.

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Why do you want to work as a Sr. Data Scientist at Visa?

Connect your career aspirations, your passion for analytics, and your interest in Visa’s mission. Discuss what excites you about the opportunity to contribute to risk and identity solutions and how your background aligns with the company’s goals.

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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
December 12, 2024

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