Data Analyst
EXL Gurugram, Haryana, India
Job Description
"Unlock the secrets of data analysis and propel your career as a Data Analyst at EXL, where your analytical prowess and SQL expertise will drive business growth and uncover hidden patterns."
As a Data Analyst at EXL, you will be at the forefront of business decision-making, leveraging your analytical mindset, SQL skills, and Excel expertise to uncover insights that drive growth and profitability.
With a strong focus on fraud experience in the banking domain, you will be responsible for performing quick and accurate data analysis to identify patterns and trends, and develop data-driven solutions to mitigate risk and improve business outcomes.
Why you should learn this:
The demand for Data Analysts is on the rise, with a projected growth of 14% by 2028, according to the Bureau of Labor Statistics.
Expected Salary: The average salary for a Data Analyst at EXL ranges from $70,000 to $110,000 per annum, depending on experience and qualifications.
How it works:
- Gather and analyze data from various sources, including databases and spreadsheets, to identify trends and patterns.
- Develop and implement data-driven solutions to mitigate risk and improve business outcomes, using tools such as SQL and Excel.
Core Concepts to Master
SQL Fundamentals
Understand the basics of SQL, including querying databases, creating and modifying tables, and indexing data. Learn to write efficient and effective SQL queries to extract insights from large datasets.
Excel Intermediate Skills
Develop advanced Excel skills, including data modeling, pivot tables, and macro development. Learn to create interactive dashboards and reports to present findings to stakeholders.
Fraud Detection and Prevention
Understand the principles of fraud detection and prevention in the banking domain, including identifying red flags, analyzing data patterns, and developing predictive models to mitigate risk.
Interview Questions (Beginner)
- What is your experience with SQL, and how have you used it to analyze data?
- Can you describe a time when you had to extract data from a large dataset and present findings to stakeholders?
- What do you know about fraud detection and prevention in the banking domain?
Job Overview
Advance Questions
- • How would you approach data modeling and analysis for a complex business problem?
- • Can you describe a time when you used pivot tables and charts to present findings to stakeholders?
- • How would you develop a predictive model to detect fraudulent activity in the banking domain?