Sr. Data Scientist (Advance SQL & Python + Spark + ML (overall workflow) + Power BI/Tableau)

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Bengaluru, Bengaluru Urban, Karnataka
In-Office
Fintech • Information Technology • Payments
Join a world leader in payments and technology!
The Role
Company Description

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world.

Progress starts with you.

Job Description

Visa cards play a crucial role in allowing our commercial solutions partners to pay and be paid. From large enterprises to small businesses, companies depend on Visa to allow their employees ease of operation in the digital payments ecosystem and to provide them with services that can help them gain valuable insights into their customers spending as well as their own spending. The Global Data Science group supports these commercial 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 hiring Data Scientists who are equally passionate about the opportunity to use Visa’s rich data to solve meaningful business problems.

Essential Functions 

  • Brainstorm innovative ways to use our unique data to answer business problems

  • Use LLM-based systems for natural language processing, data quality evaluation, and performance evaluation

  • 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

  • Identify and create key metrics and dashboards to track program success

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

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

  • Work collaboratively with Data Scientists, Data Engineers and other cross-functional partners to tailor analyses and solutions to the needs of the business

  • 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, and other business outcomes

  • Synthesize ideas/proposals in writing and engage in productive discussions with external or internal partners

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

Qualifications

Basic Qualifications
4 years of work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Master’s, MBA, JD, MD) or 0 years of work experience with a PhD degree
Preferred Qualifications
6-8 years of work experience with a Bachelor’s Degree or 4-6 years of work experience with an Advanced Degree (e.g. Master’s, MBA, JD, MD) or 3 years of experience with a PhD
4+ years’ experience in data-based decision-making or quantitative analysis
Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field
Extracting and aggregating data from large data sets using SQL/Hive or Spark
Analyzing large data sets using programming languages such as Python, R, SQL and/or Spark
Generating and visualizing data-based insights in software such as Tableau
Advanced knowledge and experience of AI/ML model development and implementation
Experienced with building AI/ML model pipelines and creating robust and scalable AI/ML solutions.
Experience working with LLMs in a production environment
Track record of creating robust and scalable AI/ML/Data Science solutions and products

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.

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The Company
HQ: San Francisco, CA
33,000 Employees
Year Founded: 1958

What We Do

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges,
growing your skills and seeing your contributions impact lives around the world.

Join Visa and do work that matters – to you, to your community, and to the world.

Progress starts with you

For more information, visit visa.com/about, @LifeatVisa Instagram, and @VisaNews on X.

Why Work With Us

At Visa, every voice powers progress. We believe inclusion fuels innovation — and that unique perspectives create better outcomes for our teams, our business, and the world we serve. With more than 13K members across our Employee Resource Groups, you’ll find community, allyship, and opportunities to lead, learn and make an impact beyond your desk.

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