Interesting Data Gigs # 13: Data Scientist at VISA

Marcos Ortiz
10 min readSep 21, 2022


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Hello Data people.

Today, I’m very happy because I have the privilege to write about one of my favorite businesses of all time: VISA.

But, I’m even more excited because thanks to an incredible member of my network of contacts, I have access to the actual team hiring for the role I’m writing about today: Data Scientist at VISA.

For all that: a massive shout-out to Celinda Farías Appleby, who is a Director of Global Talent Attraction at VISA, a proud Latina, and a big advocate of developing talent.

Celinda was a key player in the work with this article because she was the one who asked several Data Scientists inside the company to answer some of my questions to put here.

So, thank you again Celinda from the bottom of my heart.

And of course, thanks to anyone involved in this as well: Sophie, Fiyin, Elizabeth, Kelsy, Lawson, Yun (Eudora), Alicia, and many more.

Let’s talk about some interesting facts about VISA

I don’t want to dig deeper into VISA, because there are so many resources out there to do this.

I will share here some of my favorite ones:

And of course, we can’t talk about VISA and let this out:

As you can see, VISA is a big conglomerate, but they are trying to keep the pace of fintech these days, and they are looking for brilliant people to build the fintech infrastructure of the future:

Let’s talk about some interesting facts about the VISA Consulting and Analytics team

This particular team is very, very interesting, and if you visit its dedicated website, you will find something like this:

Visa Consulting and Analytics (VCA) is the payments consulting arm of Visa.

We are a global team of several hundred payments consultants and data scientists across six continents.

Our consultants are experts in strategy, product, portfolio management, risk, digital and more with decades of experience in the payments industry.

Our data scientists are experts in statistics, advanced analytics and machine learning with exclusive access to insights from VisaNet, one of the largest payment networks in the world.

The combination of our deep payments consulting expertise and our breadth of data allows us to identify actionable insights and recommendations that drive better business decisions.

I truly believe that as a Data Scientist you will thrive inside this team. Why?

Many reasons:

  • You will have access to one of the biggest payment networks in the world
  • Massive data to interact with = massive opportunities you could unlock here
  • Your work will have a direct impact on the VISA’s business and its partners’ businesses as well

My top recommendation here? Download some of the best whitepapers written by this team, and understand how they work, what matters to them, and more.

Here are some of my favorite ones:

Some Q&A from the team

As I shared before, Celinda and the team at VISA shared some incredible insights about the dynamics of the team.

I will share their answers to some of the questions I made them.

What is it like to be a Data Analytics inside the Visa Consulting and Analytics team at VISA?

30% Communication: Before we start doing the project, we need to communicate with the client and consultant and know the goal of this project. Along with the project going, we need to explain the analysis results to the consultant, and they will build corresponding strategies based on the data.

30% Coding: Using different tech stacks (SQL, Python, Spark) to pull the data you need, performing statistical analysis, or building machine learning models to solve the problem.

30% Analytics and Visualization: Analysing the benchmarking result and model result, and creating a visualization plot to make the result more readable is another major part of our daily work.

10% Self-development and Group Study: Apart from the project, we also have multiple committees including the Social Committee, Coding Committee, and a variety of study groups, we can join based on our interests. And we could also participate in conferences or take online classes by using our training budget!

What is the favorite thing you love to be part of this team?

We can be exposed to different kinds of projects. It’s a great opportunity for people who want to try out different things and you can always learn something new from different projects. For example, I did a tableau dashboard project, a modeling project, and a benchmarking project last year, and my tech stack got extended from those projects!

What drives you every single day to work at VISA?

We all know that data foundation is critical as the basis for all the analysis. VisaNet transaction-level data can provide integrated and timely data for our client and our data scientist can perform various reporting and analytics based on that.

Can you share some details about the data tech stack at VISA?

The tech stack depends on what kind of project you are working on.

The most common execution engine is Spark or Tez and a querying layer like Hive or Presto.

Spark SQL in Python is the most popular choice for the ETL tool.

Business intelligence and visualization tool are also an important part of our daily work, Tableau and Power BI are always the first choice.

Why is this role needed now, and what are you looking for in potential candidates?

Apart from the basic DS skill we listed in the job description, there are three more attributes we are looking for.

Passion: Passion is always the most important attribute when we look for a potential candidate. We will spend 1/3 of one day at work and we want you to enjoy this job!

Creative: Visa has the data foundation for all the analysis, but we also need creative data scientists to think out of the box and create new solutions for our clients.

Communication: Data Scientists in VCA need to work with the consultant to help the client solve their problems, the ability to communicate effectively with others and get along with different types of personalities will be a desirable quality in the job.

Some amazing insights here. Great communication skills + passion could help you to get this incredible role at VISA.

Let’s talk about the position

You can find the position here. Let’s dissect it piece by piece

To ensure that Visa’s payment technology is truly available to everyone, everywhere requires the success of our key bank or merchant partners and internal business units.

The Global Data Science group supports these partners by using our outstandingly rich data set that spans more than 3 billion cards globally and collects more than 100 billion transactions in a single year.

Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. We work in complementary teams comprising members from Data Science and various groups at Visa.

To support our rapidly growing group we are looking for Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to seek significant business problems.

You will join one of the Data Science focus areas (e.g., banks, merchants & retailers, digital products, marketing) with an opportunity for rotation within Data Science to gain broad exposure to Visa’s business.

You can understand from these numbers here that you will work with massive waves of data at VISA.

Essential Functions

Be an out-of-the-box problem solver who is passionate about brainstorming innovative ways to use our outstanding data to answer business problems

Connect with clients to understand the challenges they face and convince them with data

Extract and understand data to form an opinion on how to best help our clients and derive relevant insights

Develop visualizations to make your sophisticated analyses accessible to a broad audience

Find opportunities to craft products out of analyses that are suitable for multiple clients

Work with partners throughout the organization to find opportunities for using Visa data to drive business solutions.

Mine and analyze data from company databases to drive optimization and improvement of product, marketing techniques and business strategies for Visa and its clients

Assess the efficiency and accuracy of new data sources and data gathering techniques.

Develop custom data models and algorithms to apply to data sets.

Use predictive modeling to increase and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes.

Develop processes and tools to monitor and analyze model performance and data accuracy.

You will be challenged here but in a good way. You will be challenged to reach your full potential as a Data Scientist.

Preferred Qualifications

2+ years’ experience in data-based decision-making or quantitative analysis

Bachelor’s degree in an analytical field such as statistics, operations research, economics, computer science or many others (graduate degree is a plus)

Experience with extracting and aggregating data from large data sets using SQL or other tools

Competence in Excel, PowerPoint and Tableau

Experience in understanding and analyzing data using statistical software (e.g., Python, SAS, R, Stata or others)

Previous exposure to financial services, credit cards or merchant analytics is a plus, but not required

It’s time for the ideas now to stand out in your job application here.

Let’s discuss two ideas on how to approach this job application (THE REAL MEAT)

Idea # 1: Participate in a Kaggle competition and share your notebook with the world (Bonus points if it’s related to payments)

Why Kaggle?

It’s very simple: from my perspective, this is the best definition of “Building in public“ for a Data Scientist.

Being active at Kaggle could bring you a lot of visibility, and if your work is good; it will be recognized by the incredible group of experts inside the platform.

There are so many datasets related to Payments and many public notebooks that you could use as your guides to upload your own.

If you have never done anything related to Kaggle, my recommendation is this incredible book about the topic written by two Kaggle Grandmasters Konrad Banachewicz and Luca Massaron.

And of course: follow the work of other amazing Kaggle grandmasters like Ruchi Bathia, Bojan Tunguz, John Miller, Andrada Olteanu, Shize Zu, Gabriel Preda, and many more.

And of course: follow the work of other amazing Kaggle grandmasters like Ruchi Bathia, Bojan Tunguz, John Miller, Andrada Olteanu, Shize Zu, Gabriel Preda, and many more

Idea # 2: Reach out to the team, especially Celinda and Sophie

Celinda and Sophie are the primary contacts for this particular position, so feel free to contact them on LinkedIn and ask about it.

They will be more than excited to answer your questions about it.

BTW, take notes from this post from Celinda:

Celinda’s post on LinkedIn

Celinda’s post on LinkedIn

Good luck with your application, buddy.

Interesting resources of the week

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As one of the new AWS Community Builders, this will be my main contribution to the word spreading of AWS tech.

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Final words

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Marcos out.