Hi everyone, this topic is for sharing Preparation guidelines and interview experience for Cipla Data Scientist
The Data Scientist at Cipla involves a multi-stage assessment and interview process, designed to evaluate both technical skills and business proficiency. Below is a summary of the process and key points from the interviews you provided:
Assessment Test Rounds:
Resume Shortlist
Initial screening to ensure the resume is concise and highlights relevant skills/experience.
Assignment Round
Task: Build a house price prediction model, assessing coding, applied ML, and practical problem-solving.
Interview Rounds:
HR Interview
Focus on background, motivation, and communication skills.
Sample prompts included: Tell me about yourself; previous job details; reason for change; company fit/motivation.
Technical Interview (Round 1)
Experience-based deep dive; basic evaluation of working knowledge; practical examples from prior projects.
Technical Interview (Round 2)
Further discussion on past experience; departmental knowledge; instrumental guidelines; problem-solving; data science in the Pharma domain.
One-on-one Final
Focus on how the candidate would add value and propose new contributions/ideas to ongoing projects.
Interview Preparation Tips:
Tailor your resume to the role; keep it clear and concise.
Focus on experience-based questions; prepare practical examples from projects to demonstrate working knowledge.
Strengthen communication skills; be clear and structured in responses.
Practice coding and hands-on ML assignments.
Research the company thoroughly; be ready to articulate motivation and alignment with values and projects.
Be prepared to discuss data science applications in the Pharma domain (data types, workflows, regulations, impact).
Conduct Notes:
Highlight relevant experience with measurable outcomes; emphasize problem-solving approach.
In company-fit questions, adapt your answer to Cipla (some transcripts referenced another company by name during HR—treat as a generic “Why this company?” prompt).
Technical/Domain (Data Science in Pharma)
Tell us about your expertise.
Can you discuss your past experience and the related knowledge you gained?
What is your understanding of data, data science workflows, and their applications in the Pharma domain?
What departmental knowledge do you have that is relevant to this role?
What instrumental guidelines do you follow in your work?
How do you approach problem-solving on complex data science projects?
Coding/ML/Analytics
Build a house price prediction model. (Assignment)
Walk us through a project that demonstrates your working knowledge with practical examples (tools, algorithms, pipelines).
HR/Personality/Behavioral
Tell me about yourself.
Can you share details of your previous job?
Why are you looking for a change?
Why do you want to join the Glenmark family? [asked as-is in transcript; treat as company-fit/motivation question for Cipla]
Situational/Leadership/Decision-Making
What new contributions can you make to Glenmark with your expertise? [asked as-is in transcript; answer in the context of Cipla]
Experience/Project Deep-Dive
Walk us through your relevant experience and key projects aligned to this role.
Describe your working knowledge and how you’ve applied it in real-world scenarios.
If you have attended the process from your campus, pls share your experiences here; Please follow [guidelines](https://discuss.boardinfinity.com/t/interview-transcript-guidelines/22428?u=abhay-gupta-ebaf4123)
Application Process: I applied through Naukri.com and was interviewed in February 2024.
Interview Rounds:
Round 1 - Technical Round:
Questions Asked:
Relevant to your experience.
Basic evaluation of your working knowledge and experience.
Your Approach: I focused on highlighting my relevant experience and demonstrated my working knowledge with practical examples.
Outcome: Successfully cleared this round.
Round 2 - Technical Round:
Questions Asked:
Brief discussion about your past experience and its related knowledge.
Departmental knowledge, instrumental guidelines, and problem-solving.
Your Approach: I discussed my past projects in detail, emphasizing problem-solving skills and departmental knowledge.
Outcome: Cleared this round as well.
Preparation Tips:
Focus on experience-related questions and improve your communication skills.
Conclusion:
The interview process was smooth and focused on evaluating my practical knowledge and experience. I would advise future candidates to thoroughly prepare for experience-based questions and ensure clarity in communication.
Application Process: [Application process details not provided]
Interview Rounds:
Round 1 - HR Round:
Questions Asked:
Share details of your previous job.
Why are you looking for a change?
Tell me about yourself.
Your Approach: I answered the questions honestly, focusing on my previous experience and my motivation for seeking a new opportunity. I kept my responses concise and relevant to the role.
Outcome: Successfully cleared the HR round.
Round 2 - Assignment Round:
Task: House price prediction.
Your Approach: I approached the assignment by thoroughly understanding the problem, exploring the dataset, and applying relevant machine learning techniques to build a predictive model. I ensured my code was clean and well-documented.
Outcome: Submitted the assignment and awaited feedback.
Round 3 - Technical Round:
Questions Asked:
About data, data science, and the Pharma domain.
Your Approach: I discussed my understanding of data science principles and how they could be applied in the pharmaceutical industry, highlighting any relevant experience or knowledge.
Outcome: The round went well, and I received positive feedback.
Preparation Tips:
Focus on coding skills and practical assignments, as they are crucial for the role.
Brush up on data science fundamentals, especially in the context of the pharmaceutical domain.
Be prepared to discuss your previous work and how it aligns with the role.
Conclusion:
Overall, the interview process was smooth and well-structured. The HR round was conversational, while the assignment and technical rounds tested my practical skills and domain knowledge. I would advise future candidates to prepare thoroughly for coding tasks and be ready to discuss their experience in detail.
Application Process: Applied via Campus Placement before July 2023.
Interview Rounds:
Round 1 - Technical Round:
Questions Asked:
What was the difference between LCMS & GCMS?
Tell me the acid stable protecting reagent?
Your Approach: Focused on explaining the technical differences between LCMS and GCMS and recalling the correct acid stable protecting reagent from organic chemistry knowledge.
Outcome: Passed the round.
Round 2 - HR Round:
Questions Asked:
Why do you want to join Macleods?
Your Approach: Answered honestly about my interest in the role and how it aligns with my career goals.
Outcome: [Outcome not specified].
Preparation Tips:
Prepare the basic concepts of organic chemistry and common HR queries, especially if the role is for Process Development Research.
Conclusion:
The interview process was straightforward, with a mix of technical and HR questions. Focusing on core organic chemistry concepts and being prepared for standard HR questions helped. Future candidates should ensure they have a clear understanding of the role and company to answer HR questions confidently.
Application Process: Applied via LinkedIn and was interviewed before June 2023.
Interview Rounds:
Round 1 - One-on-one Round:
Questions Asked: Details about yourself.
Your Approach: I introduced myself, highlighting my educational background, relevant skills, and previous experiences that align with the role.
Outcome: Successfully cleared this round.
Round 2 - Group Discussion Round:
Questions Asked: Discussion related to previous experience.
Your Approach: I actively participated in the discussion, sharing insights from my past projects and how they could be relevant to the role.
Outcome: Cleared this round as well.
Preparation Tips:
Focus on articulating your experience clearly and concisely.
Be prepared to discuss how your skills align with the job requirements.
Conclusion:
The interview process was smooth, and the questions were aligned with the role. I would advise future candidates to thoroughly review their past experiences and be ready to discuss them in detail.
Application Process: The application process involved multiple rounds, starting with a resume shortlist followed by HR, technical, and one-on-one rounds.
Interview Rounds:
Round 1 - Resume Shortlist:
Details: The first round was a resume screening process. The key here was to ensure my resume was concise and highlighted relevant skills and experiences.
Outcome: My resume was shortlisted for the next round.
Round 2 - HR Round:
Questions Asked:
Why do you want to join the Glenmark family?
Your Approach: I emphasized my alignment with the company’s values and my enthusiasm for contributing to their mission.
Outcome: I progressed to the technical round.
Round 3 - Technical Round:
Questions Asked:
Tell us about your expertise.
Your Approach: I discussed my technical skills, projects, and how they align with the role of a Data Scientist.
Outcome: I was selected for the final round.
Round 4 - One-on-one Round:
Questions Asked:
What new contributions can you make to Glenmark with your expertise?
Your Approach: I highlighted innovative ideas and how my skills could add value to their projects.
Outcome: Awaiting final results.
Preparation Tips:
Ensure your resume is clear and tailored to the role.
Be ready to discuss your technical expertise in detail.
Research the company thoroughly to answer HR questions effectively.
Conclusion:
The interview process was structured and insightful. I felt well-prepared for the technical and HR rounds, but I could have researched more about Glenmark’s specific projects to tailor my answers better. For future candidates, focus on showcasing your skills and aligning them with the company’s goals.
Application Process: Applied via LinkedIn and was interviewed in July 2022.
Interview Rounds:
Round 1 - HR Round:
Questions Asked:
How do you manage stress?
What are your 3 strengths?
How do you prioritize projects?
Why are you interested in the role?
Your Approach: Answered honestly, focusing on my ability to handle stress through time management and prioritization. Highlighted my strengths relevant to the role and explained my interest in Cipla’s work.
Outcome: Passed to the next round.
Round 2 - Technical Round:
Questions Asked:
Behavioral question: Tell me a time when you had to work on multiple projects and what was the outcome.
Questions based on your previous experiences.
Your Approach: Shared a specific example of juggling multiple projects, emphasizing organization and results. Discussed past experiences relevant to the role.
Outcome: Advanced to the final round.
Round 3 - One-on-one Round:
Questions Asked:
Behavioral questions: Conflict management, time management, career progression.
Your Approach: Provided examples of handling conflicts professionally, managing time efficiently, and my vision for career growth.
Outcome: Successfully cleared the round.
Preparation Tips:
Do thorough research about the company.
The interviewers were very friendly, so stay calm and confident.
Conclusion:
The overall interview experience was positive. The interviewers were approachable, and the questions were fair. I would advise future candidates to prepare well for behavioral questions and understand the company’s background to align their answers accordingly.
Application Process: [Application process details not provided]
Interview Rounds:
Round 1 - Technical Round:
Questions Asked:
Q1. Can you explain your current project and your role in it?
Your Approach:
I provided a detailed overview of my current project, highlighting my contributions, the technologies used, and the impact of the project. I also discussed any challenges faced and how I overcame them.
Outcome:
Successfully cleared this round.
Round 2 - One-on-one Round:
Questions Asked:
Q1. General discussion about my experience and skills.
Your Approach:
I engaged in a conversation about my past experiences, key skills, and how they align with the role. I also asked questions about the team and the company culture.
Outcome:
Moved to the next round.
Round 3 - HR Round:
Questions Asked:
Q1. Discussion about salary expectations.
Your Approach:
I shared my salary expectations based on industry standards and my experience level. I also expressed flexibility and openness to negotiation.
Outcome:
The round concluded positively, and I received feedback on the next steps.
Preparation Tips:
Focus on clearly articulating your project details and contributions.
Be prepared to discuss your technical skills and how they apply to the role.
Research the company and role to align your answers with their expectations.
Conclusion:
The interview process was smooth and well-structured. I felt prepared for the technical and one-on-one rounds, but I could have researched more about the company’s recent projects to tailor my answers better. My advice to future candidates is to practice explaining your projects concisely and confidently, and always be ready for salary negotiations.
Application Process: I applied via a job portal and was interviewed before July 2022.
Interview Rounds:
Round 1 - Resume Shortlist:
Questions Asked: N/A (Resume screening round)
Your Approach: Ensured my resume was concise and highlighted relevant skills and experiences.
Outcome: Successfully shortlisted for the next round.
Round 2 - Technical Round:
Questions Asked:
How to maintain Data integrity?
What is product development and task?
Your Approach: Answered the questions with practical examples and explained concepts clearly.
Outcome: Cleared the technical round.
Round 3 - HR Round:
Questions Asked:
What is your salary expectation?
Why do you want to change companies?
Your Approach: Provided a realistic salary expectation and a genuine reason for seeking a change.
Outcome: Successfully cleared the HR round.
Preparation Tips:
Focus on strengthening technical skills, especially in data integrity and product development.
Improve interpersonal skills for the HR round.
Conclusion:
The interview process was smooth, and I felt well-prepared for each round. I could have researched more about the company’s specific projects to tailor my answers better. For future candidates, I recommend being thorough with technical concepts and practicing clear communication.
Application Process: Applied via Naukri.com and was interviewed before August 2023.
Interview Rounds:
Round 1 - One-on-one Round:
Questions Asked: Experience discussion.
Your Approach: Shared details about my previous roles, projects, and how my experience aligns with the Data Scientist position.
Outcome: Successfully cleared the round.
Round 2 - Group Discussion Round:
Questions Asked: Experience-related questions and some chemistry topics.
Your Approach: Actively participated in the discussion, shared insights from my experience, and contributed to the chemistry-related topics as well.
Outcome: Cleared this round.
Round 3 - HR Round:
Questions Asked: Experience discussion.
Your Approach: Reiterated my experience and how it fits the role, along with my enthusiasm for joining Cipla.
Outcome: Successfully cleared the HR round.
Conclusion:
The interview process was smooth, and the questions were mostly focused on my experience and how it aligns with the role. Being well-prepared about my past projects and staying confident during the discussions helped me clear all rounds. For future candidates, I’d recommend thoroughly reviewing your experience and being ready to discuss how it applies to the role you’re interviewing for.
Your Approach: I answered honestly, highlighting my previous experience and reasons for seeking new opportunities.
Outcome: Successfully cleared the HR round.
Round 2 - Assignment Round:
Task: House price prediction.
Your Approach: I worked on the assignment using my coding and data science skills, ensuring a practical and efficient solution.
Outcome: Cleared the assignment round.
Round 3 - Technical Round:
Questions Asked:
About data, data science, and the Pharma domain.
Your Approach: I discussed my understanding of data science applications in the pharmaceutical industry.
Outcome: Cleared the technical round.
Preparation Tips:
Focus on coding skills and practical assignments.
Be prepared to discuss data science applications in the Pharma domain.
Conclusion:
The interview process was smooth, and the questions were aligned with the role. Practicing coding and understanding domain-specific applications helped me perform well. For future candidates, I recommend brushing up on practical assignments and being clear about how data science can add value in the Pharma sector.