Scientific data or Data Scientist is the latest professional profile. It considered a key in the technology field.

What does a Data Scientist do?

The tasks that make up his day to day are the following:

• Interact with business users so that they transmit their knowledge needs to be more competitive or respond to a functional need.
• Search for data in the company and make it available for analysis.
• Analyze business data, find the most important and capture the ones that can provide value.
• Cleaning of the data, to give it an analyzable structure and resolve inconsistencies.
• Design and creation of models and algorithms using Machine algorithm tool, generating learning schemes that allow feedback to the chosen algorithms.
• Creation of reports and graphs that show the behavior of this data, so that business users can draw conclusions from the work of the data scientist.
• Help with the implementation of these conclusions in the company's systems so that better decisions are made.

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Preparation for Data Science interview

Since nobody knows very well what a Data Scientist is, it is difficult to prepare for such an interview. Just look at the job offer to see where the shots can go depending on the occasions. Follow these steps.

• Programming

Solve a typical programming problem (queues, stacks, linked lists, hashes, etc.) with a language you know.

• Data management exercises

Use R / Python or the like to read and transform a data series and do some kind of exploration. For example, taking graphs that summarize the data, doing a test to validate a hypothesis, or doing a regression that explains a certain variable.

• Database exercises

From several tables, do several operations with SQL to obtain some value, using joins, group by, etc.

• Statistical questions

From what differentiates the mean from the median to what types of statistical tests can be used in certain problems, or explains how linear regression works.

• Machine learning questions

Types of algorithms, which ones would you use in which problems, the difference between supervised / unsupervised learning, etc

• Product/intuition questions

 For example, what kind of metrics would you use to demonstrate that a certain product is successful or not? If a company is going to launch a question/answer service, what variables would we be interested in following to know that the product is working or how could we launch several proposals and choose the most successful one based on those variables?

Data Science Interview Question

Preparing for a job interview is very important because it will allow you to send a professional and competent image to the recruiter and that is what companies really look for competent professionals.

In order to help you succeed in your interview, there are some questions to prepare for a Data Scientist job interview.

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Basic Questions Asked In A Data Scientist Job Interview

1. Describe the role of Data Scientist?

Interview questions are often asked about the role of the data scientist. Data Scientists help companies understand data and solve complex problems using their sophisticated skills in data analysis.

Data scientists analyze and visualize data and facilitate its transmission to the client. They have knowledge and experience in computer science, data modeling, statistics, analytics, and mathematics, as well as business knowledge related to the area of expertise of the company (Finance, Marketing or others).

2. Define Data Science

Data science is the combination of Machine Learning or Machine Learning algorithms, tools and techniques that help find common hidden patterns from raw data.

3. List the main components of a Data Science project.

Here are the main components of a Data Science project:

• Understanding of operational requirements
• Data acquisition and preparation
• Data analysis, visualization, and inference

4. What does logical regression mean in Data Science?

Logical regression is a method of predicting the binary result from a linear combination of predictor variables.

5. Name three types of biases that can occur during sampling

In the sampling process, there are three types of bias:

• Selection
• Undercover
• Survival

6. What is the purpose of the decision tree algorithm?

The decision tree is a supervised learning algorithm. It is used for regression and classification. This allows a data set to be divided into smaller subsets. The decision tree can manage both categorical and numeric data.

7. What do past probability and likelihood mean?

The prior probability is the proportion of the dependent variable in the data set, while the likelihood is the probability of classifying a given observer in the presence of another variable.

8. What are the recommendation systems?

Recommendation systems represent data filtering. They predict user preferences on products for sale. With this preference, recommendation systems can recommend a product or service to the user.

The recommendation system is widely used to recommend films, reading articles, products, and music.

9. Name three disadvantages of the linear model

The three disadvantages of the linear model are:

• The linearity assumption of errors.
• You cannot use this model for binary results or counts
• In this model, there are several Overfitting or overflow issues that it cannot solve

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Interview Question For Senior Data Scientists

These include:

Where the data set will be unusable?

Reveals analytical skills and data cleaning. And the ability to prevent the usage of the data sets.

Describe the Data analytic techniques. Do you proudest of?

High light the commitment and expertise to skills development.

If any of the staff members suffered from loss, what would you do for him?

It testifies your commitment to producing a sense of community and specifically the interpersonal skills.

How much time did you take to develop capacity in your coworkers?

In answer to this question, you have to describe the training skills