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Salesforce Data Scientist Interview Questions and Answers

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Interview Questionnaire 

1 Question

  • Q1. What PCA, Decision tree and computer vision
  • Ans. 

    PCA is a dimensionality reduction technique, decision tree is a classification algorithm, and computer vision is a field of study focused on enabling computers to interpret and understand visual information.

    • PCA is used to reduce the number of variables in a dataset while retaining the most important information.

    • Decision trees are used to classify data based on a set of rules and conditions.

    • Computer vision involves usin...

  • Answered by AI

Skills evaluated in this interview

I applied via Campus Placement and was interviewed before Sep 2020. There were 3 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Nothing much technical

Interview Preparation Tips

Interview preparation tips for other job seekers - 1. Go in formals
2. Fluency in English is important (depends on interview panel)
3. Clarity on what your talking about

I applied via Referral and was interviewed in Mar 2021. There were 4 interview rounds.

Interview Questionnaire 

2 Questions

  • Q1. What is data science
  • Ans. 

    Data science is the field of extracting insights and knowledge from data using various techniques and tools.

    • Data science involves collecting, cleaning, and analyzing data to extract insights.

    • It uses various techniques such as machine learning, statistical modeling, and data visualization.

    • Data science is used in various fields such as finance, healthcare, and marketing.

    • Examples of data science applications include fraud...

  • Answered by AI
  • Q2. What is phyton and R
  • Ans. 

    Python and R are programming languages commonly used in data science and statistical analysis.

    • Python is a general-purpose language with a large community and many libraries for data manipulation and machine learning.

    • R is a language specifically designed for statistical computing and graphics, with a wide range of packages for data analysis and visualization.

    • Both languages are popular choices for data scientists and hav...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Provide the tips how to face the interview

Skills evaluated in this interview

Interview Questionnaire 

1 Question

  • Q1. Please tell me something about yourself.What is your experience? What are your goals and ambitions?Why We should hire you? Strengths and weaknesses etc.
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via LinkedIn and was interviewed before Apr 2023. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. How does fbpropher forecasting model works and how is can be used to forecsst trafffic
  • Ans. 

    fbprophet is a forecasting model developed by Facebook that uses time series data to make predictions.

    • fbprophet is an open-source forecasting tool developed by Facebook's Core Data Science team.

    • It is based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.

    • fbprophet can be used to forecast traffic by providing historical data on traffic patterns and usi...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Thourough with maths of forecasting techniques and parameter tuning
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Approached by Company and was interviewed in Aug 2023. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. How can Logistic regression be applied for multiclasstext classification
  • Ans. 

    Logistic regression can be applied for multiclasstext classification by using one-vs-rest or softmax approach.

    • One-vs-rest approach: Train a binary logistic regression model for each class, treating it as the positive class and the rest as the negative class.

    • Softmax approach: Use the softmax function to transform the output of the logistic regression into probabilities for each class.

    • Evaluate the model using appropriate...

  • Answered by AI

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Properly align and format text in your resume. A recruiter will have to spend more time reading poorly aligned text, leading to high chances of rejection.
View all tips
Round 2 - Coding Test 

2 coding questions - one on binary tree and list operations.

Round 3 - Technical 

(2 Questions)

  • Q1. Xgboost explanation
  • Ans. 

    Xgboost is a popular machine learning algorithm known for its speed and performance in handling large datasets.

    • Xgboost stands for eXtreme Gradient Boosting, which is an implementation of gradient boosted decision trees.

    • It is widely used in Kaggle competitions and other machine learning tasks due to its efficiency and accuracy.

    • Xgboost is known for its ability to handle missing data, regularization techniques, and parall...

  • Answered by AI
  • Q2. Data structures question compulsory

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
6-8 weeks
Result
Selected Selected

I applied via Company Website and was interviewed before Mar 2023. There was 1 interview round.

Round 1 - One-on-one 

(3 Questions)

  • Q1. Explain L1 & L2 regularization
  • Ans. 

    L1 & L2 regularization are techniques used in machine learning to prevent overfitting by adding a penalty term to the cost function.

    • L1 regularization adds the absolute values of the coefficients as penalty term (Lasso regression)

    • L2 regularization adds the squared values of the coefficients as penalty term (Ridge regression)

    • L1 regularization encourages sparsity in the model, while L2 regularization tends to shrink the c...

  • Answered by AI
  • Q2. Explain error metric
  • Ans. 

    Error metric is a measure used to evaluate the performance of a model by comparing predicted values to actual values.

    • Error metric quantifies the difference between predicted values and actual values.

    • Common error metrics include Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared.

    • Lower values of error metric indicate better performance of the model.

    • Error metric helps in und...

  • Answered by AI
  • Q3. Where do you see yourself

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via Company Website and was interviewed before Mar 2023. There were 3 interview rounds.

Round 1 - HR 

(2 Questions)

  • Q1. Resume related questions on project experiences
  • Q2. Check technical stack, whether you have the right tech skills
  • Ans. 

    Yes, I have the right tech skills for the Data Scientist role.

    • Proficient in programming languages like Python, R, and SQL

    • Experience with data visualization tools like Tableau or Power BI

    • Knowledge of machine learning algorithms and statistical analysis techniques

    • Familiarity with big data technologies like Hadoop and Spark

  • Answered by AI
Round 2 - Technical 

(2 Questions)

  • Q1. Basic ml concept
  • Q2. Details of machine learning projects and how to deal with communication, prioritization issues
Round 3 - Coding Test 

Simple leetcode type sql, python questions

I applied via Naukri.com and was interviewed in Apr 2022. There were 4 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Don’t add your photo or details such as gender, age, and address in your resume. These details do not add any value.
View all tips
Round 2 - Group Discussion 
Pro Tip by AmbitionBox:
Don’t treat group discussions as an argument. Group discussion is about reaching a meaningful conclusion.
View all tips
Round 3 - Technical 

(2 Questions)

  • Q1. How do you work towards a random forest?
  • Ans. 

    To work towards a random forest, you need to gather and preprocess data, select features, train individual decision trees, and combine them into an ensemble.

    • Gather and preprocess data from various sources

    • Select relevant features for the model

    • Train individual decision trees using the data

    • Combine the decision trees into an ensemble

    • Evaluate the performance of the random forest model

  • Answered by AI
  • Q2. What is bias variance trade-off
  • Ans. 

    Bias-variance trade-off is the balance between overfitting and underfitting in a model.

    • Bias is the error due to assumptions made in the learning algorithm. Variance is the error due to sensitivity to small fluctuations in the training set.

    • High bias leads to underfitting, while high variance leads to overfitting.

    • The goal is to find the sweet spot where the model has low bias and low variance, which results in good gener...

  • Answered by AI
Round 4 - HR 

(2 Questions)

  • Q1. Tell me about your self
  • Ans. 

    I am a data scientist with expertise in machine learning and data analysis.

    • I have a strong background in statistics and mathematics.

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

    • I have experience working with large datasets and extracting insights from them.

    • I have developed predictive models for various industries, including finance and e-commerce.

    • I am skilled in data visualization and communicating com

  • Answered by AI
  • Q2. Why you are perfect for this job
  • Ans. 

    I have a strong background in data analysis and machine learning, with a proven track record of delivering actionable insights.

    • I have a Master's degree in Data Science and have completed several projects involving data analysis and predictive modeling.

    • I am proficient in programming languages such as Python and R, as well as in using tools like TensorFlow and Tableau.

    • I have experience working with large datasets and hav...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Interview should be basics as well as are friendly environment

Skills evaluated in this interview

Salesforce Interview FAQs

How to prepare for Salesforce Data Scientist interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Salesforce. The most common topics and skills that interviewers at Salesforce expect are Salesforce, Analytics, Data Analysis, SQL and Automation.

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