Data Scientists Making $100k Monthly. Here’s How!

In this article, We will explain you to how data scientists work. And why you should have to learn to get $100k monthly. If you are a beginner or if you dose not have much knowledge about the data scientist. So, you should definitely read this article. I will teach you by using an effective way.

What is Data Science or Data Analysing with a Scenario?

Let’s Imagine, Emma is a data scientist let’s see how a day inner life goes while she’s working on the data science project. It is very important to understand the business problem first. In our meeting with the clients, Emma asks relevant questions to understands and defines objectives for the problem that needs to be tackled. she is a purist soul who asks a lot of ice and It is one of the main features of a good data scientist. 

Now, she cares up for data acquisition to gather and scrape data from multiple sources like SAP servers logs, databases API’s and online repositories. It seems like finding the right data. Both takes time and effort. After the data is gathered then comes to data preparation step involves data cleaning and data transformation. 

Data Cleaning

It is the most time-consuming process. It involves handling many complex scenarios to deals with inconsistent data types Misspelt Attributes, Missing Values and DuplicateValues.

Data Transformation

Data transformation use for modifies the data based on defined mapping rules in a project. ETL tools like Talend and Informatica are used to perform complex transformations. Although, It improves the team to understand the data structure better than understanding. 

What you actually can do with your data is essential for that Emma does exploratory data analysis with the help of EDA. She defines and refines the selection of feature variables that will be used in moral development.  

Data analysis becomes the most important step. Now, she proceeds to the core activity of a data science project such as data modelling. She repetitively applies type force machine learning techniques

1.KNL

2. Decision-tree 

3. Naive Bayes

Identify Data

Use for the data to identify the moral that best fits the business requirement. she trains the models on the training data set and tests them to select the best performing model. They recommend  Python for modelling the data. however, it can also be done by using R and SAS.

Also, over visualization and communication, Emma meets the clients again to communicate the business and findings in a simple and effective manner to convince the stakeholders she uses tools like Tableau, Power bi and QlikView that can assist her in creating powerful reports and dashboards.

Finally, she deploys and maintains the model. she tests the selected model in a pre-production environment before deploying it in the production environment which is the best practice right after successfully deploying it. she use reports and dashboards to get real-time analytics. Further, she also monitors and maintains the projects performance well that is how Emma completes the data science project.

Daily Routine of a Data Scientist

We have seen the daily routine of a data scientist is a whole lot of fun, has a lot of interesting aspects and comes with its own share of challenges. Although, let’s see how data science is changing the world data science techniques along with genomic data provides a deeper understanding of genetic issues in reaction to particular drugs and diseases. 

The Usage of Data Scientists In Big Companies

Logistic companies like DHL, FedEx have discovered the best routes to ship, the best suited time to deliver, the best mode of transport to choose thus leading to cost efficiency with data science. it is possible to not only predict employee attrition. but also understand key variables that influence employee turnover. Also, the Airline companies can now easily predict flight and notify the passengers beforehand to enhance their travel experience.

Jobs and Salary

If you are wondering there are various rules offered to a data scientist like Data Analyst, Machine Learning Engineer, Deep learning, Ingenio Data Engineer and data scientist the median base salaries of the data scientists can range from 95k Dollars to 165k Dollars. 

Conclusion

That was about data science are you ready to be a data scientist if yes then start today. The world of data needs you. 

That’s all from my side, comment below on the next topic that you want to learn?

Thank You and Keep Learning