Data Analyst II, RM - AMER
Criteo Gurgaon, Haryana, India
Job Description
"Join Criteo's Analytics team as a Data Analyst II, RM - AMER, and drive business growth through data-driven insights."
As a Data Analyst II, RM - AMER at Criteo, you will play a crucial role in turning business requests into actionable data problems, leveraging your technical skills in SQL, Excel, Hive, Python, and other leading-edge data tools.
You will collaborate with analyst teams across Criteo locations, working on technically rigorous projects that require a strong understanding of data analysis and business acumen.
Why you should learn this:
High demand for data analysts in the US market, with a projected growth rate of 14% by 2028 (BLS)
Expected Salary: $80,000 - $120,000 per year, depending on experience and location (Indeed)
How it works:
- Develop a deep understanding of business requirements and translate them into data problems
- Design and implement scalable and efficient data solutions using SQL, Excel, Hive, Python, and other data tools
- Collaborate with cross-functional business units to perform back-office data analysis and reporting
Core Concepts to Master
Data Modeling
Learn to design and implement data models that accurately represent business requirements and enable data-driven insights
Data Visualization
Master the art of data visualization using tools like Tableau, Power BI, or D3.js to effectively communicate insights to stakeholders
Machine Learning
Discover the power of machine learning algorithms and apply them to real-world business problems using Python libraries like scikit-learn or TensorFlow
Interview Questions (Beginner)
- What is your experience with SQL, and how have you used it to solve business problems?
- Can you walk me through a time when you had to analyze a large dataset and identify key insights?
- How do you stay up-to-date with the latest developments in data analysis and visualization?
Job Overview
Advance Questions
- • Design a data architecture to support a complex business requirement. Walk me through your thought process and decisions.
- • You are given a large dataset with multiple variables. How would you approach feature engineering and selection?
- • Can you explain the concept of data governance and how it applies to a large organization like Criteo?