Data Scientist
Data Scientist
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
To ensure that Visas 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 Visas 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 Visas business.
The role will be based in Bengaluru India
Essential Functions
Be an outofthebox 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
Bachelors or Masters 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 bachelors degree or 4 years experience with an advance degree (e.g. Masters 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 databased decisionmaking 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 databased 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.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
