LKQ INDIA Interview Questions, Process, and Tips

Q1. Boxing and unboxing
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Q2. Inner joins , constraints
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Q1. Basic accounts for commerce students
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Q2. Experience persons will get questions regarding P2P cycle and credits and price issue questions
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PREPARE FROM RESUME, company financials

Q1. Why ypou want thi job
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Q2. What do u know abt lkq
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Q1. Question related to car and spare parts
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Q1. Asked about your previous experience and related questions
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Q2. Suspension parts name
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Q3. Questions regarding automobile.
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Q1. Difference between AWD and RWD
Ans. 
AWD stands for all-wheel drive, distributing power to all four wheels for improved traction. RWD stands for rear-wheel drive, powering only the rear wheels.
• AWD provides better traction in various road conditions such as snow or rain

• RWD typically offers better handling and performance in dry conditions

• AWD is commonly found in SUVs and some sedans, while RWD is more common in sports cars and trucks
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Q2. Asked for future goals.
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Q1. Interview with practice leader
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Q1. Salary discussion
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Q1. Tell me about yourself
Ans. 
I am a detail-oriented data analyst with a strong background in statistics and programming.
• Graduated with a degree in Statistics

• Proficient in programming languages like Python and R

• Experience in analyzing and interpreting data sets

• Strong attention to detail and problem-solving skills
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Q2. What inspired you to apply for this job role and how you are a good fit for the role?
Ans. 
I have always been passionate about data analysis and problem-solving, and I believe this role aligns perfectly with my skills and interests.
• I have a strong background in statistics, mathematics, and data analysis techniques.

• I have experience using various data analysis tools such as Excel, SQL, and Python.

• I enjoy working with data to uncover insights and make data-driven decisions.

• I am detail-oriented, analytical, and...read more
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Q3. How would you react if you are not selected for the job role?
Ans. 
I would thank the interviewer for the opportunity, ask for feedback, and continue my job search.
• Thank the interviewer for the opportunity

• Ask for feedback on areas of improvement

• Continue job search and apply to other positions
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Q1. MDM, Data Governance, Data Quality
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Q2. Brief on previous projects worked
Ans. 
Developed a predictive model for customer churn using machine learning algorithms
• Utilized Python for data cleaning and preprocessing

• Implemented logistic regression and random forest algorithms for model training

• Performed feature engineering to improve model performance

• Evaluated model performance using metrics such as accuracy, precision, and recall
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Q3. Advance excel, SQL
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