Data Analyst

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions, and government entities across 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.

Why Visa?

When you join Visa, you join a culture of purpose and belonging, where your growth is priority, your identity is embraced, and the work you do matters. Your work will have a direct impact on millions of people around the world – helping unlock financial access to enable the future of money movement.

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.

The position will be based in Visa’s Bangalore office, and you will be working very closely with Visa’s Data Science team in Australia and New Zealand Region. We are looking for a data analyst with experience in data preparation, data analysis, implementing data solutions, building and running data pipelines. The candidate will be working with VISA’s big data sets and in certain cases in conjunction with our clients’ data. The candidate would be responsible for end-to-end handling of technical delivery of client requirements. The candidate is expected to have hands on experience with associated technologies and ability to collaborate across teams and functions to deliver value to VISA and our clients.

S/he must have a highly analytical bent of mind and requisite skills to independently analyse and interpret data insights. We are looking for a talented, technical, proactive, energetic, and passionate person who embraces challenges and is a proven problem solver.

What is Visa Consulting & Analytics?

Visa Consulting & Analytics (VCA) Data Science team is a key part of the Global Data Solutions organization, a high-performing team of data scientists, data analysts and data engineers 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. Our focus lies on building creative solutions that empower our clients.

Principal Responsibilities

• Partner with roles across the organization including consultants, data engineering, and data scientists to address prioritized business problems.
• Build data driven solutions aligned with stakeholder priorities and leading different vendors for the execution if required.
• Break large solutions into smaller, releasable milestones and seek feedback from product managers, clients, and other stakeholders.
• Define detailed scope and methodology, design and create solutions, and execute leveraging appropriate tools and techniques.
• Support development of a robust data quality framework for measuring and optimising the quality of deployed data solutions.
• Make sure that the legal/compliance/security related requirements are fully adhered to.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Basic Qualifications and Experience

• Minimum of bachelor’s degree or equivalent
• Qualification in Data Analytics/Data Engineering/Computer Science.
• 3+ years of relevant experience being data scientist/analyst or analytics consultant.
• Hands-on experience in scaling data solutions and delivering end-to-end data science projects.
• Proficient in big data aggregation using Hive, PySpark, SQL, Python
• Experience with complex, high volume, multi-dimensional data.
• Outstanding problem-solving skills, with demonstrated ability to think creatively and strategically.
• Strong internal team and stakeholder management with a collaborative, and flexible style, able to work effectively in a matrixed organization
• Exhibit intellectual curiosity and strive to continually learn, self-motivated and results oriented individual with the ability to handle numerous projects.
• Progressive learner with ability to learn new tools and paradigms as data science continues to evolve at Visa and elsewhere.
• High performance delivery focus with a high attention to detail
• Good communication and presentation skills
• Understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchant will be a plus.
• Consulting experience is a plus.

Technical Expertise

Primary:

• Proficient in writing and optimizing efficient SQL queries and Python/PySpark for data science.
• Experience with complex, high volume, multi-dimensional data
• Experience in big data ecosystem like Hadoop and Hive
• Good understanding of Agile way of working, tools such as JIRA and practical experience of working in Agile teams.

Secondary:

• Expertise in dashboard and report development using tools such as Tableau/Power BI
• Experience on creation and automation of data pipelines using Airflow and Tuber will be an added advantage
• Experience creating data story and proficiency in using power point
• Experience of cloud-based data science platforms will be an added advantage

Business and Leadership competencies

• Results-oriented with strong problem-solving skills and demonstrated intellectual and analytical rigor.
• Team oriented, collaborative and flexible.
• Detail oriented to ensure highest level of quality/rigor in reports and data analysis.
• Exhibits intellectual curiosity and a desire for continuous learning.

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.