Onsite
Full Time Posted 8 days ago
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Job Type

Full Time

Job Details

Job Description

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 extraordinarily rich data set that spans more than 3 billion cards globally and captures 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 tackle meaningful 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.

The role will be based in Bengaluru, India

Essential Functions

· Be an out-of-the-box thinker who is passionate about brainstorming innovative ways to use our unique data to answer business problems

· Communicate 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 complex analyses accessible to a broad audience

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

· Work with stakeholders throughout the organization to identify opportunities for leveraging 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 effectiveness 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

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, and reach with hands and arms.

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


Qualifications

Basic Qualifications

· Bachelor’s or Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field

· 5+ years of work experience with a bachelor’s degree or 4+ years’ experience with an advance degree (e.g., Master’s or MBA)

· Analyzing large data sets using programming languages such as Python, R, SQL and/or Spark

· Developing and refining machine learning models for predictive analytics, classification and regression tasks.

Preferred Qualifications

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

· Knowledge of ETL pipelines in Spark, Python, HIVE that process transaction and account level data and standardize data fields across various data sources

· Generating and visualizing data-based insights in software such as Tableau

· Competence in Excel, PowerPoint

· Previous exposure to financial services, credit cards or merchant analytics is a plus


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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Data Scientist
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