JP MORGAN CHASE IS hiring Freshers for the roles of DATA SCIENCE ANALYST. The details of the job, requirements and other information given below:
JP MORGAN CHASE IS HIRING : DATA SCIENCE ANALYST
- Qualification : Any Bachelor’s Degree
- Freshers or individuals with up to 2 years of work experience with an engineering or equivalent background are welcome.
- Excellent hands-on skills in AI/ML, Python, Alteryx, PEGA workflow.
- Intermediate knowledge of Python.
- Intermediate knowledge of PEGA workflow.
- Intermediate experience using Microsoft Office suite, including Excel, Visio, and PowerPoint
- Location: Bengaluru, Karnataka, India
Don’t miss out, CLICK HERE (to apply before the link expires)
Interview Questions and Beginner-Friendly Answers
1. What is the role of a Data Science Analyst in an operations team?
Answer:
As a Data Science Analyst, your role is to use data to make operations better. You’ll look at how processes work, find places where time or effort is wasted, and help improve them using automation, AI tools, or better planning. You will also help analyze data to support business decisions.
2. What tools and technologies are you familiar with?
Answer:
I have worked with Python for data analysis and basic machine learning. I’m learning or have basic experience with tools like Alteryx and PEGA for automation. I also use Excel for organizing data and PowerPoint to present my results. I’m currently exploring AI/ML concepts and how they apply in real business cases.
3. Explain a simple automation project you have done (or would like to do).
Answer:
In a project, I used Python to read and clean Excel files and create summary reports automatically. This saved a lot of time compared to doing it manually. If I get a chance, I’d like to create a simple chatbot that uses NLP to answer customer support questions using a dataset of common issues and answers.
4. What is low-code/no-code automation?
Answer:
Low-code/no-code automation means building software or workflows without writing a lot of code. Tools like Alteryx or PEGA let you create automation using drag-and-drop options. This helps non-programmers create solutions quickly and allows faster development.
5. What is NLP (Natural Language Processing)?
Answer:
NLP is a part of AI that helps computers understand and work with human language. For example, it allows systems to understand text, answer questions, or translate languages. It’s used in tools like chatbots, voice assistants, and search engines.
6. What is the difference between AI and ML?
Answer:
AI (Artificial Intelligence) is the broad idea of making machines smart, like humans.
ML (Machine Learning) is a part of AI that teaches machines to learn from data and improve over time without being programmed for every task.
Example:
AI is like building a robot that plays chess.
ML is when the robot learns how to play better every time it plays a game.
7. How do you handle a large amount of messy data?
Answer:
First, I check the data to find issues like missing values or errors. Then, I clean the data using tools like Python (Pandas) or Excel — I remove duplicates, fill in missing values, and format it properly. Clean data helps in making better and more accurate analysis.
8. Why do you want to work in this role at J.P. Morgan?
Answer:
J.P. Morgan is known for using advanced technologies to solve real-world problems. I’m excited about working in data, automation, and AI because they have the power to improve business decisions. I also want to learn from experienced teams and grow in a global company like J.P. Morgan.
9. How do you stay updated with new technologies like LLMs or AI?
Answer:
I follow online courses, read blogs on platforms like Medium and Towards Data Science, and watch YouTube tutorials. I also try to build small projects to practice what I learn. I recently read about how LLMs like ChatGPT are used in customer support and document analysis, which I found very interesting.
10. What is PEGA, and how is it used in automation?
Answer:
PEGA is a low-code automation platform that helps build business applications fast. It’s used for tasks like handling customer requests, workflow automation, and reducing manual work. It saves time and improves efficiency by using drag-and-drop interfaces with minimal coding.
Final Tips for Applicants
Know the tools mentioned in the job post: Python, Alteryx, PEGA.
Even if you haven’t used them deeply, show interest and willingness to learn.
Practice simple Python data analysis tasks (pandas, NumPy).
Understand basic AI/ML and automation concepts.
Be ready to explain your thought process clearly — even for small projects or assignments.
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