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Boston Scientific Senior Data Analyst Interview Questions and Answers

Updated 22 May 2021

Boston Scientific Senior Data Analyst Interview Experiences

1 interview found

I applied via Naukri.com and was interviewed in Nov 2020. There were 5 interview rounds.

Interview Questionnaire 

4 Questions

  • Q1. About my role and responsibilities?
  • Q2. Area of expertise?
  • Q3. My background?
  • Q4. Focus on professional, less personal.

Interview Preparation Tips

Interview preparation tips for other job seekers - What I learnt over the year, always pratice in what to ans and how? Give positive response and stay true as much as you can.most of the question asked from the current role, so if you true to your self you will get it through. Good luck!!

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. SQL,Aptitude Questions
  • Q2. Logical Questions,case studies
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

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

Round 1 - Coding Test 

2 questions based on coding

Round 2 - Technical 

(2 Questions)

  • Q1. Reverse a string
  • Ans. 

    Reverse a given string

    • Use built-in functions like reverse() or slice() in Python

    • Iterate through the string in reverse order and append each character to a new string

    • Convert the string to an array of characters, reverse the array, then join the characters back together

  • Answered by AI
  • Q2. Linked list in java
  • Ans. 

    A linked list is a data structure in Java where each element points to the next element in the list.

    • Linked list nodes contain data and a reference to the next node

    • Insertion and deletion operations are efficient in linked lists

    • Traversal requires iterating through each node starting from the head

    • Example: Node class with data and next pointer, LinkedList class with methods to insert, delete, and traverse

  • Answered by AI

Skills evaluated in this interview

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

I applied via Campus Placement and was interviewed in Jul 2023. There were 2 interview rounds.

Round 1 - Aptitude Test 

It was basic aptitude but it was online

Round 2 - Technical 

(1 Question)

  • Q1. Write python code for bizzbuss for prime or not prime\
  • Ans. 

    Python code for determining if a number is prime or not and applying bizzbuzz logic.

    • Write a function to check if a number is prime or not

    • Iterate through a range of numbers and apply bizzbuzz logic

    • Return 'prime' if the number is prime, 'bizz' if divisible by 3, 'buzz' if divisible by 5, and 'bizzbuzz' if divisible by both 3 and 5

  • Answered by AI

Skills evaluated in this interview

I applied via Recruitment Consulltant and was interviewed in Sep 2022. There were 4 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 - Technical 

(2 Questions)

  • Q1. Random forest splitting mechanisms details
  • Ans. 

    Random forest uses decision trees to split data into subsets based on feature importance.

    • Random forest builds multiple decision trees and selects the best split based on feature importance.

    • Each decision tree splits data into subsets based on a randomly selected subset of features.

    • The best split is determined by minimizing impurity or maximizing information gain.

    • Random forest can handle missing values and outliers.

    • Rando...

  • Answered by AI
  • Q2. ResNet architecture and skip connection related questions
Round 3 - Technical 

(2 Questions)

  • Q1. OCR related bounding box detection from image
  • Q2. Deep learning based questions and details
Round 4 - HR 

(2 Questions)

  • Q1. Salary discussion, current salary and expected
  • Q2. About Optum, why you want to join

Interview Preparation Tips

Interview preparation tips for other job seekers - Go through data science basics and python coding. Prepare deep learning Pretrained architecture as well.

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Easy
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Naukri.com

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 - Technical 

(1 Question)

  • Q1. Tableau Top 100 Question
Round 3 - Technical 

(1 Question)

  • Q1. Tableau and SQL related questions.
Round 4 - HR 

(1 Question)

  • Q1. Salary Discussion and how early u can join that kind of question.

Interview Preparation Tips

Interview preparation tips for other job seekers - If u know Excel then it's plus point for you because they are working on excel most.

I applied via Naukri.com and was interviewed before Oct 2020. There were 3 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. 1) Model building process of one of my previous projects 2) Random forest hyperparameters 3) ROC curve, using the ROC curve to set probability cutoffs in classication models 4) Gradient boosting techniques...
  • Ans. 

    Data Scientist interview questions on model building, random forest, ROC curve, gradient boosting, and real estate valuation

    • For model building, I followed the CRISP-DM process and used various algorithms like logistic regression, decision trees, and random forest

    • Random forest hyperparameters include number of trees, maximum depth, minimum samples split, and minimum samples leaf

    • ROC curve is a graphical representation of...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - My advice would be to search on Google regarding "100 data science interview questions" or something like it, and as you go through each question and its answer, just search the Wikipedia or Google for each concept for a little more depth. As for Python coding questions, most questions in such interviews are asked only about the Pandas library of Python. So try to study how to use Pandas to manipulate data. A good reference is the Python For Data Analysis book by Wes McKinney, whose free PDF is most probably available online on Google.

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. What is random forest
  • Ans. 

    Random forest is an ensemble learning method used for classification and regression tasks.

    • Random forest is a collection of decision trees that are trained on random subsets of the data.

    • Each tree in the random forest independently predicts the target variable, and the final prediction is made by averaging the predictions of all trees.

    • Random forest is robust to overfitting and noisy data, and it can handle large datasets...

  • Answered by AI
  • Q2. Bias variance trade off

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. SQL,Aptitude Questions
  • Q2. Logical Questions,case studies
Interview experience
5
Excellent
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 - Technical 

(1 Question)

  • Q1. Fundamentals of ML, classical ML
  • Ans. 

    Fundamentals of classical machine learning

    • Classical machine learning involves algorithms that learn from data and make predictions or decisions.

    • Common algorithms include linear regression, decision trees, support vector machines, and k-nearest neighbors.

    • Key concepts include training data, testing data, model evaluation, and hyperparameter tuning.

    • Classical ML is often used for tasks like classification, regression, clus

  • Answered by AI
Round 3 - Technical 

(1 Question)

  • Q1. Research paper discussion

Skills evaluated in this interview

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₹13 L/yr - ₹16.6 L/yr
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