- Hiring Organization: RBC
- Post Name: Data Analyst
- Industry: Financial services
- Qualification: 12th Pass
- Salary: CAD 10 to CAD 20 Per Hour
- Job Experience: 0 to 1 Years
- Work Hours: 8 Hours
- Employment Type: Full-time
- Location: Toronto, Canada
Royal Bank of Canada (RBC; French: Banque royale du Canada) is a Canadian multinational financial services company and the largest bank in Canada by market capitalization. The bank serves over 16 million clients and has 86,000+ employees worldwide. Founded in 1864 in Halifax, Nova Scotia, it maintains a corporate headquarters in Toronto and its head office in Montreal. RBC’s institution number (or bank number) is 003. In November 2017, RBC was added to the Financial Stability Board’s list of global systemically important banks.
In Canada, the bank’s personal and commercial banking operations are branded as RBC Royal Bank in English and RBC Banque Royale in French and serves approximately ten million clients through its network of 1,209 branches. RBC Bank is the U.S. banking subsidiary which formerly operated 439 branches across six states in the Southeastern United States, but now only offers cross-border banking services to Canadian travelers and expats. RBC also has 127 branches across seventeen countries in the Caribbean, which serve more than 16 million clients. RBC Capital Markets is RBC’s worldwide investment and corporate banking subsidiary, while the investment brokerage firm is known as RBC Dominion Securities. Investment banking services are also provided through RBC Bank and the focus is on middle market clients.
A data analyst gathers, cleans, and studies data sets to help solve problems. A data analyst collects, cleans, and interprets data sets in order to answer a question or solve a problem. They can work in many industries, including business, finance, criminal justice, science, medicine, and government.
- Analyzing data using statistical techniques and providing reports.
- Developing and implementing databases and data collection systems.
- Acquiring data from primary and secondary sources and maintain data systems.
- Identifying, analyzing, and interpreting trends or patterns in complex data sets.
- Microsoft Excel.
- Critical Thinking. .
- R or Python–Statistical Programming.
- Data Visualization.
- Presentation Skills.
- Machine Learning.
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