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Ford Motor Senior Data Science Analyst Interview Questions and Answers

Updated 15 Mar 2024

Ford Motor Senior Data Science Analyst Interview Experiences

1 interview found

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Feb 2024. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Tell me about your project
  • Q2. Explain the difference between a decision tree and a random forest
  • Ans. 

    Decision tree is a single tree model while random forest is an ensemble of multiple decision trees.

    • Decision tree is a single tree model that makes decisions based on splitting data into branches at each node.

    • Random forest is an ensemble of multiple decision trees that make predictions by averaging the results of individual trees.

    • Decision tree tends to overfit the training data while random forest reduces overfitting by...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Mostly focus on resume and ML question

Skills evaluated in this interview

Interview questions from similar companies

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I was interviewed in Mar 2024.

Round 1 - Coding Test 

45 mins 15 min mcq data science and 30 mins 1 dsa problem

Round 2 - Technical 

(5 Questions)

  • Q1. Python - All subsets of a list.
  • Ans. 

    Generate all possible subsets of a given list in Python.

    • Use itertools.combinations to generate all possible combinations of the list elements.

    • Convert the combinations to lists and store them in a new list to get all subsets.

  • Answered by AI
  • Q2. Sql query - Customers who have ordered all products from all categories.
  • Ans. 

    Use a SQL query to find customers who have ordered all products from all categories.

    • Join the Customers, Orders, and Products tables

    • Group by customer and count the distinct products ordered

    • Filter for customers who have ordered the total number of products available in each category

  • Answered by AI
  • Q3. Importance of feature engineering.
  • Ans. 

    Feature engineering is crucial in data science as it involves selecting, transforming, and creating new features to improve model performance.

    • Feature engineering helps in improving model accuracy by providing relevant and meaningful input variables.

    • It involves techniques like one-hot encoding, scaling, normalization, and creating interaction terms.

    • Feature engineering can help in reducing overfitting and improving model...

  • Answered by AI
  • Q4. Questions on project.
  • Q5. What is GAN.Have you worked with it.
  • Ans. 

    GAN stands for Generative Adversarial Network, a type of neural network used for generating new data.

    • Consists of two neural networks - generator and discriminator

    • Generator creates new data samples while discriminator tries to distinguish between real and generated data

    • Used in image generation, text generation, and other creative applications

  • Answered by AI
Round 3 - Technical 

(7 Questions)

  • Q1. Discussion on project.Demo of project.
  • Q2. Analysis sql query - whether class 11 marks or class 12 marks is greater., table given which contains student name,class,11th marks,12th marks.
  • Q3. Similar table. Find students who scored more than avg marks of both 11th and 12th.
  • Ans. 

    Find students who scored more than avg marks in both 11th and 12th grades.

    • Calculate the average marks for each student in 11th and 12th grades.

    • Compare each student's marks with the respective average marks to find those who scored higher in both grades.

  • Answered by AI
  • Q4. What is Cost function.
  • Ans. 

    Cost function is a mathematical function that measures the error between predicted values and actual values in a machine learning model.

    • Cost function helps in optimizing the parameters of a model to minimize the error.

    • Common cost functions include Mean Squared Error (MSE) and Cross Entropy Loss.

    • It is used in training machine learning models through techniques like gradient descent.

    • The goal is to find the parameters tha

  • Answered by AI
  • Q5. What is entropy.
  • Ans. 

    Entropy is a measure of disorder or randomness in a system.

    • Entropy is used in information theory to quantify the amount of uncertainty involved in predicting the value of a random variable.

    • It is often used in machine learning to measure the impurity or disorder in a dataset.

    • In thermodynamics, entropy is a measure of the amount of energy in a physical system that is not available to do work.

  • Answered by AI
  • Q6. What is ginni coefficient.
  • Ans. 

    Gini coefficient is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation's residents.

    • Gini coefficient ranges from 0 to 1, where 0 represents perfect equality and 1 represents perfect inequality.

    • A Gini coefficient of 0.4 is considered moderate inequality, while 0.6 or higher is considered high inequality.

    • It is commonly used in economics to measure income inequality with...

  • Answered by AI
  • Q7. What will happen if linear regression is used for classification
  • Ans. 

    Using linear regression for classification can lead to inaccurate predictions and unreliable results.

    • Linear regression assumes a continuous output, making it unsuitable for discrete classification tasks.

    • It may not handle outliers well, leading to incorrect classification boundaries.

    • The predicted values may fall outside the 0-1 range for binary classification.

    • Logistic regression is a more appropriate choice for classifi

  • Answered by AI
Round 4 - One-on-one 

(2 Questions)

  • Q1. Pair sum problem in python.Discussion on space time complexity.
  • Q2. Discussion on project.What algorithms used and why.

Skills evaluated in this interview

Interview experience
2
Poor
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Company Website and was interviewed in Mar 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Artificial intelligence and python

Round 2 - Technical 

(4 Questions)

  • Q1. Artificial intelligence, python
  • Q2. Machine learning
  • Q3. What is AI and what is neural network and types
  • Ans. 

    AI stands for Artificial Intelligence, which is the simulation of human intelligence processes by machines. Neural networks are a type of AI that mimic the way the human brain works.

    • AI is the simulation of human intelligence processes by machines.

    • Neural networks are a type of AI that mimic the way the human brain works.

    • Types of neural networks include feedforward neural networks, convolutional neural networks, and recu

  • Answered by AI
  • Q4. What is ml and regression and classification
  • Ans. 

    ML stands for machine learning, a subset of artificial intelligence that focuses on developing algorithms to make predictions or decisions based on data. Regression and classification are two types of supervised learning techniques in ML.

    • ML is a subset of AI that uses algorithms to make predictions or decisions based on data

    • Regression is a type of supervised learning used to predict continuous values, such as predictin...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Mahindra & Mahindra Data Science Engineer interview:
  • Artificial Intelligence
  • Python
Interview preparation tips for other job seekers - I am data science course in progress

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via LinkedIn and was interviewed in Feb 2023. There were 2 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Data Science 

(3 Questions)

  • Q1. Can you work under pressure?
  • Ans. 

    Yes, I can work under pressure.

    • I have experience working on tight deadlines and delivering high-quality results.

    • I am able to prioritize tasks and manage my time effectively.

    • I remain calm and focused in stressful situations.

    • I can adapt to changing priorities and handle multiple projects simultaneously.

  • Answered by AI
  • Q2. Where do you see yourself after 2/3/4/5 years?
  • Ans. 

    In 2/3/4/5 years, I see myself as a senior data scientist leading a team, solving complex problems, and driving impactful insights.

    • Leading a team of data scientists

    • Solving complex problems using advanced analytics techniques

    • Driving impactful insights for business decision-making

    • Continuously learning and staying updated with the latest advancements in data science

    • Contributing to the growth and success of the organizatio

  • Answered by AI
  • Q3. Why should we hire you?
  • Ans. 

    I have a strong background in data science and a passion for problem-solving, making me a valuable asset to your team.

    • I have a solid foundation in data science concepts and techniques.

    • I am proficient in programming languages such as Python and R.

    • I have experience working with various data analysis and visualization tools.

    • I am a quick learner and adapt easily to new technologies and methodologies.

    • I have excellent proble...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - We are pleased to inform you that you have been selected for an interview for the position of [Job Title] at [Company Name]. Our team was impressed with your qualifications and experience, and we believe that you would be a great fit for the role.

The interview will take place on [Date] at [Time] at our office located at [Address]. Please plan to arrive 10-15 minutes before the scheduled interview time to allow for check-in and any necessary paperwork.

During the interview, you will have the opportunity to meet with members of our team and learn more about the position and the company. You will also have the chance to ask any questions you may have about the role or the organization.

Please confirm your availability for the interview by replying to this email or by contacting us at [Contact Information]. If you need to reschedule, please let us know as soon as possible so that we can make the necessary arrangements.

Ford Motor Interview FAQs

How many rounds are there in Ford Motor Senior Data Science Analyst interview?
Ford Motor interview process usually has 1 rounds. The most common rounds in the Ford Motor interview process are One-on-one Round.

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