EY Global Delivery Services ( EY GDS) Technical Lead Interview Questions, Process, and Tips

Experience is the knowledge and skills acquired through participation in various activities or exposure to different situations.

• Experience can be gained through work, education, travel, or personal challenges.

• It helps individuals develop expertise, problem-solving abilities, and decision-making skills.

• Employers often value candidates with relevant experience in a particular field.

• For example, a software developer may h...read more

I have over 10 years of technical experience in software development, project management, and team leadership.

• Proficient in various programming languages such as Java, Python, and JavaScript

• Extensive experience in designing and implementing scalable and robust systems

• Strong background in database management and optimization

• Skilled in leading cross-functional teams and driving project delivery

• Hands-on experience with cl

Inheritance is a concept in object-oriented programming where a class can inherit attributes and methods from another class.

• Allows for code reusability by creating a new class based on an existing class

• Child class inherits properties and behaviors of the parent class

• Can have multiple levels of inheritance

• Example: Class Animal can be a parent class with subclasses like Dog and Cat inheriting its attributes and methods

Azure ADLS stands for Azure Data Lake Storage, a scalable and secure data lake solution for big data analytics.

• Azure ADLS is a cloud-based storage solution provided by Microsoft Azure.

• It is designed for big data analytics workloads, allowing users to store and analyze large amounts of data.

• ADLS offers features like high availability, scalability, and security for data storage and processing.

• It supports various data typ...read more

XGBoost is implemented by installing the library, loading the data, defining the model parameters, training the model, and making predictions.

• Install the xgboost library using pip or conda

• Load the data into DMatrix format for efficient processing

• Define the model parameters such as learning rate, max depth, and number of trees

• Train the model using the fit() function

• Make predictions using the predict() function