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Data Scientist - Credit Card Analytics (3-5 yrs)

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

About Visa Consulting & Analytics.

Visa Consulting and Analytics (VCA) is Visa's consulting division, serving Visa's clients (including card issuers, acquirers and merchants) and solving their strategic problems focused on improving performance and profitability. Drawing on our expertise in strategy consulting, payments, data analytics, marketing, operational and macroeconomics, VCA drives high impact and tangible financial results.

The individual will be part of VCA Data Science team, under Managed Services vertical and will be responsible for delivering data analytics projects with Visa client. The team is involved in a comprehensive range of analytics services for our client, that address unique challenges in areas such as strategic growth, cards profitability, product acquisitions, customer engagement and portfolio management.

What a Data Scientist, Visa Consulting & Analytics does at Visa:

The Data Scientist will be a member of VCA Data Science team in Asia Pacific and will report to the squad lead. This position will be embedded at client office and based in Bangalore.

The individual will be accountable for delivery and implementation of analytics strategies as well as high-impact solutions for the client. He/she will bring in deep expertise from retail banking and credit cards with a strong background in data analysis to solve complex problems and unlock business value.

Key responsibilities include:

  • Execute and deliver data analytics projects for the Visa client
  • Drive credit card acquisition strategies with the use of client data and/or other sources of data e.g. Visa data, third party etc.
  • Act as analytics advocate within our partners, advising and coaching teams and sharing best practices and case studies.
  • Continually look at the environment to challenge our assumptions around new sources of data, potential analytics partners, tools, talent and infrastructure.
  • Explore leading methodologies, best practices and import successful methodologies from other international markets
  • Effectively interact with clients and manage internal/external stakeholder communication

Why this is important to Visa

As payments consulting arm of Visa, VCA is growing a team of highly specialized experts who can provide best-in-class payment expertise and data-driven strategies to clients. We’re building a high-performing team of data scientists, data analysts and statisticians helping major organizations adapt and evolve to meet the changes taking place in technology, finance, and commerce with cutting-edge, creative and advanced analytic solutions. The purpose of the team is to help Visa’s clients grow their business and solve problems by providing consulting services through the use of data. 

What you will need:

We are looking for a motivated, analytical minded individual with a track record of using data and analytics to unlock business value. A successful candidate should have accumulated a variety of industry experience, be curious about banking and cards industry, should be results-driven and client-centric.

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:
2-4 years of relevant work experience with a Bachelor’s Degree in Computer
Science or related field or an advanced degree in Computer Science or related
field

Preferred Qualifications:
MS in Computer Science or related field
Degree in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent
3-5 years of analytics experience in applying statistical solutions to business problems
Experience in card payments and/or retail banking domain
Hands on experience with one or more data analytics/programming tools such as SAS/Hadoop/R/SQL/Python/Hive
Outstanding problem-solving skills, with demonstrated ability to think creatively and strategically
Presentation and data storytelling skills including strong hold on MS Excel and PowerPoint
Self-motivated, results oriented individual with ability to handle multiple projects concurrently
Experience in working closely with data science community

Additional Information

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.

Average salary estimate

$75000 / YEARLY (est.)
min
max
$60000K
$90000K

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 Data Scientist - Credit Card Analytics (3-5 yrs), Visa

Are you passionate about data and its impact on the world of credit cards? Join Visa as a Data Scientist in Credit Card Analytics and make your mark in the financial services landscape! Based in the vibrant city of Bangalore, this hybrid role allows you to work collaboratively with clients and internal teams to deliver top-notch data analytics projects. At Visa, a leader in payments technology, our mission is to connect the world through the most innovative and secure payments network, and as part of the Visa Consulting & Analytics team, you'll play a crucial role in achieving that goal. Your responsibilities will involve leveraging your expertise in retail banking and credit cards to drive strategic insights and improve client performance. You will be involved in everything from executing credit card acquisition strategies to coaching teams in best practices, all while fostering high-impact solutions that unlock business value. Collaboration and creativity are at the heart of our work, as you will challenge existing assumptions about data sources and explore new methodologies to elevate client success. With your analytical mindset and client-centric approach, you will help major organizations adapt to the rapidly changing finance landscape. Ready to take the next step in your career? We would love to hear from you!

Frequently Asked Questions (FAQs) for Data Scientist - Credit Card Analytics (3-5 yrs) Role at Visa
What are the primary responsibilities of a Data Scientist - Credit Card Analytics at Visa?

As a Data Scientist specializing in Credit Card Analytics at Visa, your primary responsibilities include executing data analytics projects, driving credit card acquisition strategies, and serving as an analytics advocate for client teams. You'll be tasked with delivering high-impact solutions and working closely with clients to address their unique challenges in areas like strategic growth and customer engagement.

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What qualifications do I need to apply for the Data Scientist - Credit Card Analytics position at Visa?

To apply for the Data Scientist - Credit Card Analytics position at Visa, you should have a Bachelor's or advanced degree in a related field, along with 3-5 years of analytics experience. Experience in the card payments or retail banking domain is preferred, along with proficiency in data analytics tools such as Python, R, or SQL, and outstanding problem-solving skills.

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What tools and technologies should a Data Scientist at Visa be familiar with?

As a Data Scientist at Visa, you should be comfortable using data analytics and programming tools such as SAS, Hadoop, R, SQL, Python, and Hive. Familiarity with data storytelling and presentation software like MS Excel and PowerPoint is also important for effectively communicating your analysis and findings.

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How does Visa support professional development for Data Scientists?

Visa is committed to professional development, offering opportunities for Data Scientists to enhance their skills through ongoing training, mentorship, and collaboration with a community of data science experts. This environment fosters learning and growth, ensuring you remain at the forefront of the industry.

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What makes working at Visa as a Data Scientist unique?

Working at Visa as a Data Scientist is unique due to the impactful nature of our consulting services in the financial sector. You will have the opportunity to shape strategies and create data-driven solutions that help clients grow their businesses while experiencing a dynamic and inclusive work culture that values innovation and collaboration.

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Common Interview Questions for Data Scientist - Credit Card Analytics (3-5 yrs)
Can you explain a project where you utilized data analytics to solve a business problem?

In preparing for this question, focus on a specific project where your analysis led to actionable insights. Describe the problem, the data you worked with, the methodologies you applied, and the impact your work had on the business outcomes.

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How do you prioritize multiple analytics projects with competing deadlines?

When addressing this question, emphasize your organizational and time management skills. Discuss your approach to assessing project priorities based on timelines, client needs, and potential business impact, as well as how you communicate with stakeholders to align on expectations.

Join Rise to see the full answer
Describe a challenging data analysis problem you encountered and how you resolved it.

Utilize the STAR method (Situation, Task, Action, Result) to outline a specific challenge. Highlight the complexity of the data, the strategies you employed to overcome obstacles, and the positive results that followed your efforts.

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What programming languages and tools are you proficient in, and how have you used them in past projects?

Be specific about your technical skills, mentioning the programming languages and tools relevant to the role at Visa. Discuss your experience with each, providing examples of how you applied them to derive insights or solve problems in previous projects.

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How do you approach learning new data analytics techniques?

Share a proactive approach to learning, highlighting any specific resources you utilize such as online courses, workshops, or professional networks. Emphasize your curiosity and commitment to continuously improving your skill set to stay relevant in the field.

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Can you provide an example of how you effectively communicated complex data findings to non-technical stakeholders?

Illustrate your ability to distill complex data insights into digestible information. Mention specific tools or techniques you use to visually represent data, as well as your strategies for ensuring that your audience understands the implications of your findings.

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What strategies do you use to validate your data analysis results?

Discuss the importance of validation in your process, including cross-referencing findings with other data sources, performing sensitivity analyses, or seeking feedback from colleagues. Highlight your meticulous approach to ensuring accuracy.

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What role does collaboration play in your data analysis process?

Emphasize the significance of teamwork in analytics projects, sharing how you collaborate with different teams to gather insights, test assumptions, and refine approaches. Discuss any tools or methods you use to facilitate effective communication.

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How do you stay updated with the latest trends and advancements in data science?

Speak about the importance of staying informed in such a rapidly evolving field. Mention professional organizations, online communities, or publications you follow, and discuss any recent trends in data science that you find particularly relevant to the role at Visa.

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

Express your enthusiasm for the role and the company’s mission. Discuss your alignment with Visa’s values and how you see this position as an opportunity to leverage your skills to contribute significantly to the company's consulting efforts in the financial sector.

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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
March 27, 2025

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