Career opportunities in Data science

After spending your evenings, late night studies, done so many projects and assignments on Data Analytics course, now the time has come for the Interview with good companies.

Now you want to get a job. Which, despite your best efforts as a data analyst, depends almost entirely on acing the interview.

After doing so much hard work, it should be careful preparation, and understanding the expectations going into the process, is what it takes not only to survive an interview for a Data Analyst position but to set yourself apart as the best-qualified candidate.

Here are some quick tips that you should have in mind while preparing for the Interview:

Knowing Your Field Quite Well –

Some of the favourite questions that might come again and will be like-

  • What do you think a data scientist is/does?
  • What do you think are the most important skills for a data scientist to have?

In this case, you’ll have to craft your answers thoughtfully not only showing your interests and your commitment to Data Job but also your soft skills and your way of Communication as well. You might be having the Interview with HR with no technical Background, so in this case, no need to explain the theoretical concepts of Data Analysis rather, talk about yourself, your interests apart from Data, your strengths and weaknesses etc.

While facing Interview with technical HR, you need to explain your answers in broad. Some common questions that you might face may be like –

  • How to model a quantity that you can’t directly observe (using Bayesian approaches, for example, and when doing so, how to choose prior distributions).
  • The various numerical optimization techniques (maximum likelihood, maximum a posteriori).
  • The tradeoffs between different types of classification models. Between different types of regression models.
  • Which machine learning model (classification vs. regression, for example) to use given a particular problem.
  • How to go about training, testing, and validating results. Different ways of controlling for model complexity.
  • What types of data are important for a particular set of business needs, how you would go about collecting that data.

Get prepared for your interview and by the time you can google the latest trends and questions in Data Analyst Job Interview.

Brush Up Beforehand

Being able to talk fluently and confidently across the range of tools and methods of data analysis means a fair amount of study beforehand. You might find it useful to review your coursework and notes, and to go over the latest tech blogs and industry newsletters.

  • Web Scraping techniques
  • Linear/polynomial regression
  • Decision trees
  • Dimensionality reduction
  • Clustering/Classification
  • Data Visualization

Talk about Yourself

This is the time to demonstrate how you approach a data problem and how well you can report and share your results. Here the best idea is discussed, a project you really loved working on—your passion will underscore your presentation. Make sure you can explain this project well and with confidence:

  • Why you chose this model for your project work, given the problem you were trying to solve?
  • What were the key features of your data used?
  • How you tested and validated the results?
  • What techniques you used in the project?
  • What you got out of the project?

Know the Company well, you are about to Interview

Along with your skills and knowledge for Data science, recruiters are looking for interviews who will be a good fit for the company and its culture. It goes without saying that you need to do what you can to research the company you’re interviewing with, looking not only at their products, but finding out what you can about their office culture as well. Think about a few reasons you’d like to work there.

Here is another blog post which describes in detail skills and roles need to master to get hired as a Data scientist

Must be able to answer:

  • What’s a project you would want to work on at our company?
  • What data would you go after to start working on it?
  • What unique skills do you think you’d bring to the team?

You should be ready to provide relevant answers to the above questions.

Here are some General questions for entry-level Data Analysts Interview –

  1. What do data analysts do?
  2. Please talk about a time when you could not meet a deadline.
  3. Which data analysis software are you well-versed in?
  4. What was your most difficult data analyst project?
  5. What is your process when you start a new project?
  6. Why did you go into data analysis?
  7. Mention what are the various steps in an analytics project?
  8. Mention what is data cleaning?
  9. Explain what is logistic regression?
  10. What is the difference between data mining and data profiling?
  11. Mention what are the missing patterns that are generally observed?
  12. Explain what is KNN imputation method?
  13. What are the data validation methods used by Data Analyst?
  14. Explain what is an Outlier?
  15. What is Hierarchical Clustering Algorithm?
  16. What is time series analysis?
  17. Explain what is correlogram analysis?
  18. What is a hash table?
  19. What are hash table collisions? How is it avoided?
  20. Explain what is imputation? List out different types of imputation techniques?

Prepare questions like this to crack your Data Analyst Interviews and Get hired in some good company.

A data analyst uses data to acquire information about specific topics. This usually starts with the survey process, in which data analysts find survey participants and gather the needed information. The data is then interpreted and presented in forms such as charts or reports. Data analysts may also put their survey data in online databases.

Employment Opportunities in Data Science

Salary numbers are dependent on job responsibilities. A senior data analyst with the skills of a data scientist can command a high price. An entry-level Data Analyst with basic technical tools might be looking at anything from ₹405K₹430K per year.

According to a report updated on January 27, 2018, on PayScale, the highest paying data analysts jobs were in – you guessed it – San Francisco. There the median pay for analysts was $70,041 (more than 25% above the national average).

Here is a financial context for your prospects as a data analyst, according to PayScale. National salary ranges for the following data jobs:

  • Data Analyst (Entry Level): ₹3,49,484₹4,00,000
  • Data Analyst (Experienced): ₹7,36,000₹8,27,000
  • Data Scientist: ₹4,93,947₹6,20,244
  • Data Architect (Entry level): ₹4,00,000₹6,80,000
  • Data Architect (Experienced): ₹5,79,714₹ 9,40,000
  • Data Engineer (Junior): ₹6,80,448₹8,30,000
  • Data Engineer (Domain Expert): ₹7,50,550₹9,47,500

Salary opportunities in Data science | EduGrad

Each of these roles contributes critically to obtaining, analyzing, and delivering data. Embarking on a career as a data analyst gives you plenty of options down the road as you hone your skills.

It’s important to note that, given the talent crunch and the dynamic state of the data industry, compensation is far from standardized. Right now, salaries are essentially as much as a company is willing to spend to fill their immediate needs.

Industries hiring Data scientists

Companies hiring Data scientists

Where are these Job Actually Located?

Data Jobs are of course available in almost every IT hubs. Big MNC’s are hiring for Data jobs in Jaipur, Bangalore, Mumbai, Pune, Kolkata, Chennai, Hyderabad, Mysore, Delhi, Gurugram, Noida.

So here, go with your career opportunity in Data Analytics and get satisfied compensation for that.

What we are doing as EduGrad?

We are leveraging the talent gap between freshers and organizations by providing the on-demand courses in Data science to undergraduate/graduate students. We have designed the course curriculum by Industry experts which focuses on the real data problems in the industry. The courses are designed in such a way that it has to be completed in a time bound manner.  The tasks a real Data Analyst executes in a day-to-day schedule. To help out the students to give them a kick start in Data science career, we provide them one to one mentorship to clear their doubts in timely.

After the course completion, our career team helps you improvise your personality growth and communication skills with repeated mock interviews and will help you achieve your dreams.

The Bottom Line

Whether you’re contemplating a career change or just setting off in the professional world, pursuing the path of the data analyst holds serious promise for both your bank account and your brain.

Explore our Data science courses – 

Learn web scraping using Python | EduGrad Learn Data Analytics using Python | EduGrad

Learn Intro to Database tools for Data Science | EduGrad Learn Presentation skills for Data scientists | EduGrad

Our Popular Tutorials –

Learn Regression Analysis in 2 min | EduGrad Data Visualization tools and start creating your own Dashboards | EduGrad


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