Stage 1: HR/Recruiter Screening Call (15–30 minutes)
Objective: Assess communication skills, motivation, and culture fit.
Questions:
Why are you interested in this role?
Tell us about a recent data project you worked on.
What are your salary expectations and notice period?
Stage 2: Technical Assessment (Take-Home or Online Test)
Objective: Evaluate coding ability, data wrangling, and problem-solving skills.
Format: Could include a case study or dataset analysis with deliverables (code, notebook, and brief report).
Typical Tasks:
Data cleaning and EDA.
Feature engineering.
Model building (e.g., regression, classification).
Result interpretation and communication.
Stage 3: Technical Interview ( 45 minutes)
Objective: Deep dive into technical knowledge and approach.
Topics:
Python, SQL queries, Pandas, NumPy.
Machine learning algorithms and model evaluation.
Probability, statistics, and hypothesis testing.
Business case discussion or live coding.
Sometimes includes a whiteboard/diagramming session.
Stage 4: Case Study or Business Problem Discussion
Objective: Assess analytical thinking and ability to connect technical work to business outcomes.
Example Format:
Present a problem (e.g., churn prediction or sales forecasting).
Ask candidate to explain how they would approach the solution, what data they would need, potential pitfalls, etc.
Stage 5: Final Interview / Cultural Fit
Objective: Gauge alignment with company values and team dynamics.
Interviewers: Team lead, manager
Topics:
Past experiences and team collaboration.
Ethical considerations in data use.
Career aspirations and long-term goals.
Interview questions [1]
Question 1
How do you handle missing data in a dataset?
Explain the difference between apply(), map(), and applymap() in Pandas.
What is the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN?
How do you find duplicates in a table?
How do you interpret a p-value?
How do you prevent overfitting in a machine learning model?
Explain precision, recall, and F1-score.
When would you use a decision tree over logistic regression?
How would you measure the success of a recommendation system?
Imagine you're given messy, real-world data with missing values and outliers. Walk me through how you'd clean and prepare the data.
I applied through an employee referral. The process took 1 day. I interviewed at BizViz Technologies (Bengaluru) in Dec 2024
Interview
Managerial Round with questions on project or previous experience (if you have any).Questions on SQL and Python with basic knowledge in the domain. also experience in designing. Overall it was an easy round of interview process.
I applied through a recruiter. The process took 3 days. I interviewed at BizViz Technologies (Bangalore Rural) in Nov 2024
Interview
Application Review: BDB reviews submitted applications to identify potential candidates based on qualifications and experience.
Technical Assessment: This is often a coding challenge where candidates work on a problem, such as programming a robot to navigate specific tasks, which tests their coding and problem-solving skills.
Technical Interview(s): These sessions focus on coding skills, data structures, algorithms, and potentially system design. Behavioral questions are common to assess fit and teamwork capabilities.
Interview questions [1]
Question 1
OOP and Design Patterns:
Discuss the four principles of Object-Oriented Programming (OOP).
What design patterns have you used, and when would you apply them (e.g., Singleton, Factory)?
Explain dependency injection and its advantages.
Java Concurrency:
Describe synchronized keyword and how it works.
What are Callable and Future in Java concurrency?
Explain the use of ThreadPoolExecutor and its importance in Java.
Java 8+ Features:
Describe lambda expressions and provide an example.
Explain the purpose of Stream API and how it differs from traditional collections.
What is Optional, and why is it useful?
Framework-Specific Questions (Spring, Hibernate):
Explain dependency injection in Spring.
How does the Spring Boot application lifecycle work?
Discuss Hibernate ORM and how it manages database transactions.