Data Science, Data Analysis, Business Analyst, Machine Learning, Database Engineer, Deep Learning, Natural Language Processing… you would have heard these terms. And this why you are here! This field is emerging exponentially. There are lots of opportunities, lots of things to learn and explore.
I am a graduate of the Indian Institute of Technology, Kanpur. I have a great passion for data science and recently got placed as a Data Scientist in a Healthcare Startup.
What I find before and after working in this field for 3 months is:
- What we prepare, as a student, for Data Scientist is much more different than what we do as a Data Scientist. As a student, I have prepared for probability and statistics, machine learning algorithms, done some projects and internships. But as a Data Scientist, I had to work in scala with different databases and build some machine learning models.
- Python is generally used everywhere, but a new language is booming up and will surely take over python in some years. And, that is Scala. Scala is the language for huge data whose functioning is similar to Java Virtual Machine.
- Knowledge of Machine learning algorithms is not enough. There are lot more things that you will learn in the Data Science industry. An exposure to Databases like Hadoop, GitHub commands (create a repo, building the repo, git branch, git push), and SQL would be a plus. But that doesn't mean it is a must!
- To the above point, I would like to add the HR Interview preparation. In every you you need to be a good communicator. And It is not something god gifted, it can be learned with practice.
- We should be clear what are the jobs of Data Scientist, Business Analyst, Data Analyst, and Database Engineer. When you understand what a person does what works, you can excel in the field at a much faster rate. Also, this is will help you to set career goals and achieve them by minimizing useless efforts.
- Is Data Structures and Programming important for Data Science? I bet you, only experienced people can give you the best answer to this question.
After reading the above statements you would have the following question in your head:
- Ok, there is a lot to do!
- Can somebody tell me what to do, and how can I do all this?
This is where experience comes into the picture. Once you have gone through a process, you can easily make a list of do’s and don’ts and how to achieve something. A properly structured strategy not only organizes thoughts in your mind but will also increase your efficiency.
When you are organized, you can plan better, you can learn faster and you can succeed more.
So, I will share my experience and my friends too who have successfully excelled in this field.
What to Expect from this Article?
Interview preparation is an Art. It is the combination of hard work (which you have done in till now. Projects, courses, Internships, etc.) and smart work (which you will do now as the interview preparation strategy).
In a series of articles, we will try to cover the following aspects of interview preparation strategy.
1. Understanding the Field of Data Science
In this, article, we will discuss different job position and their work. We will also discuss what things we need to learn to ace in an interview in chronological order.
2. Probability and Statistics
It is a vast topic. But experience tells that for an interview some concepts are very important and are sufficient to ace the interview.
In this article, we will talk about:
- Important concepts with examples.
- What types of questions can be asked on that topic.
3. Machine Learning Algorithms
Solving an ML problem by building Ml algorithms is not sufficient. You need to have an in-depth knowledge of what is going in the background of that code.
In this article we will talk about:
- Assumptions of machine learning algorithms
- How it optimizes
- What cost functions it uses
- What error metrics we must use on which type of Dataset
- What algorithm we must use for a given data set
- Advantages and disadvantaged of ML algorithms
4. Data Structures for Data Science
Yes! we need knowledge of programming in the field of data science.
Programming tells a lot to the interviewer about you:
- How you identify and understand a problem
- How you approach your problem
- What dimensions of the problem can you think of immediately
- Can you implement your approach (what's in your head) using a language (in a form of code)
Many interviewers ask tough questions just to check your approach and temperament. They do expect a correct answer. This helps let them know that you can survive in this field or not.
5. Resume Preparation
How to make a well-standing resume is a crucial task. It is the first impression on the interviewer. Also, these pages show what we have done till now. What was our performance? Many interviewers first see the resume then frames the questions to ask. Hence, when you prepare a resume strategically, you can drive your interview yourself.
Resume preparation also includes how well you revise all your projects and courses. How explicitly you can explain your projects and internship experience. If you had done a lot in the project but cannot reflect in your interview, it would of no use.
This is a powerful tool. Hence, we must spend some time learning how to use this weapon in interviews.
6. HR Preparation
After the technical round gets over. Recruiter seeks the communication ability of students in HR rounds. HR interview is not only about yourself or your career goals. They may include logical puzzles and guesstimates.
These things are very easy. But you prepare for these things, it gives an impression of how well prepared you are. When you take an interview seriously, the interviewer will take you seriously. That's Newton’s third law.
One more thing that will help us to ace an HR interview is company research. This is no big deal, but have to find answers to some questions about the company. This will allow them to know your interest to be a part of this company.
Where are these articles?
Next question in your head, I guess!
This is a huge project. And I need to gather all my experience in a proper format. Hence whenever an article gets completed, this article will be updated, and you can see the link.
If you want to add some questions or doubts please feel free to tell me. Because, if it's your doubt, it will be of many. I try to get the best answers to your query!
All the best for the Interviews!