10 Skills that will take you Closer to your Data Science Dream

Data Science – The sexiest job of the 21st century

Data Science is one of the hottest career options these days and the demand for Data Scientists is continuously growing especially in the IT sector.

Seeing such a lucrative career field, most of the people just enter into it without even grasping proper skills and knowledge and thus, they often fail.

To become a standout Data scientist, you need to have the necessary skills and knowledge.

Along with this, you are required to remain updated with the latest market trends.

This article presents the most important skills that will take you closer to your Data Science Dream.

Top 10 Must Have Technical Skills to Become Data Scientist

1. Mathematics 

It is essential for a Data Scientist to have a strong background for mathematics.

Various concepts of mathematics such as multivariate calculus, Linear Algebra are the base of many algorithms. 

Thus implementing such algorithms will require you to have knowledge of Mathematics concepts. 

Understanding mathematics will also help you to have a strong foundation in the areas of machine learning, which is very significant and useful for Data Scientists.

2. Statistics and Probability

One of the major tasks of Data Scientists is to extract the valuable information from the collected data and make informed decisions.

The data scientists are also required to estimate, predict and conclude for decision making. 

All these tasks require the use of statistics and probability.

The techniques of statistics and probability enable us to understand the relation between variables, discover the hidden patterns, and predict future events.

Thus, statistics and probability plays an integral role for Data Scientists.

3. Python

Python is currently one of the most preferred languages for Data Science, Big Data and Machine Learning projects.

It has unique features and simple syntax that make it more popular. 

It also has various libraries and frameworks such as Pandas, NumPy, SciPy, Seaborn, MatPlotlib which are very useful for Data Scientists.

4. Other Programming Languages

Apart from Python, there are various other programming languages which a Data Scientist should be familiar with. 

These are Java, Scala, R, JavaScript, SAS, Scala.

All these languages are extremely popular and useful for executing the tasks of Data Scientists. 

Before deciding to learn any of these languages, pros and cons along with the suitability of each language with the particular industry you are seeking to enter, needs to be considered.

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5. Analytical Tools

Analytical tools such as Spark, Hadoop, and SQL provide useful frameworks for data processing.

The tools also help to extract valuable insights from data. 

Using these tools for the purpose of data processing makes the task easier and effective. 

Thus, having sufficient knowledge for handling these tools is very important to become a proficient Data Scientist.

6. Machine Learning and AI

A Data Scientist needs to be efficient in the area of Machine Learning.

You need to know various machine learning techniques such as reinforcement learning, neural networks, decision trees, logistic regression to compete with other data scientists. 

Data Scientists need to be well-versed with the technologies of Artificial Intelligence and Machine Learning. 

Data Scientists need to work with large amounts of datasets and thus it requires applications of machine learning skills.

7. Data Visualization

The collected data needs to be analyzed in order to make it worth and useful for decision-making.

Until and unless you are not able to understand the data, it is of no use. 

There are various Data visualization tools such as PowerBI, Tableau, MatPlotlib, GPlot that enable us to convert our necessary data into charts, graphs and other visuals. 

Knowledge of Data Visualizations tools helps Data Scientists to understand and analyze the overall conditions of the business in an easier manner.

And accordingly helps them to make better decisions.

8. Data Wrangling

The data you’ve collected from multiple sources is quite messy and requires to be cleaned up properly.

You need to convert the raw data into meaningful information which requires the data to be in a structured format. 

Therefore, as a Data Scientist you’re required to have the capability to work with unstructured data and find out the valuable insights out of them. 

9. Software Engineering

In order to become a Data Scientist, you need to be highly educated.

Researchers say that 88% have at least a Master’s degree and 46% have PhDs- Though there are various exceptions. 

The areas of studies are Maths and Statistics, Computer Science, and Engineering.

Completing courses in these fields will provide you with the skills necessary to process and analyze the data. 

10. Business Acumen

To become a Data Scientist, it is essential for you to have a thorough knowledge of the business industry in which you’re working. 

You must be able to identify problems which need immediate attention and find out innovative ways to solve them. 

To put all your efforts into the right direction, it is important for you to know how business operates and all the problems that it faces.

You must also be able to find out the new ways of leveraging your data.

Technically, understanding the business background will help you in maximizing efficiency, minimizing costs, and grabbing new opportunities. 

In brief, having proper business knowledge will help you generate more effective analysis.

Conclusion

It’s time to turn your Data Science dream into a reality.

These are some of the essential skills you need to possess in order to get a Data Science job.

Apart from these technical skills, there are some non-technical skills also such as communication, teamwork and intellectual curiosity which is also essential for a Data Scientist. 

Having a combination of all these skills will make a Data Scientist capable of performing his/her duties and responsibilities in an efficient manner.