Top 20 Must Have Skills for A Data Scientist

Are you looking to learn all-needed skills for a Data Scientist?

So you do know that the job of a Data Scientist is more than just being the sexiest job of the 21st century or “the highest paying jobs ever”.

You need to quickly and constantly learn new skills to be a Data Scientist that stays on top of the ever-changing trends. We’re sure you must have questions like:

  • Where should I start?
  • What should I learn to upgrade my skills?
  • How can my progress be measured?
  • How can I stay ahead of my competitors?
  • How can I be more useful to my business or the organization?

In this article, we answer all these questions for you. Read on to know the right skills to be a Data Scientist.

What are some must-have skills for a Data Scientist?

The skills to be a Data Scientist can be divided into two categories: Technical skills and Behavioral skills.

Technical Skills to be a Data Scientist

Technical tools for Data Scientist

1. Python

Python is one of the most popular programming languages as it is not tough to be mastered. The majority of the businesses and the companies use this open-source platform as the base of all their Data Science operations.

Housing large libraries that aid in Data Manipulation, Python can be easily integrated with the prevalent infrastructure. If you are ac
quainted with the programming languages like C, Java, you will not find it hard to learn this language.

One programming language for multiple platforms, Python is used across industries like banks, healthcare and IT, etc. Master this language and you will start setting your foot in the booming field of Data Science.

2. R

‘R’ is a must for figuring out answers to almost any statistical problem.

It is an open-source statistical software package that lets Data Scientists perform predictive and statistical analysis. A Data Scientist is required to be a master in dealing with the statistical and computational programming aspects using R.

Providing sturdy support for regression techniques; statistics, clustering and graphical methods, this is one of the must-have language skills to be a Data Scientist.

3. SQL

A specialized programming language used to work on data from Relational Database Management System (RDBMS), SQL functions as per its name- Structured Query Language.

Want to try out different things with data? Writing your SQL codes is the way to go!

This querying language is used when a Data Scientist is presented with the relational variables. SQL is an important skill because a Data Scientist doesn’t need to define a method to fetch a particular record. Simply access multiple records with one command.

Programming languages form the base of your Data Science career and bring along multiple benefits. Python, R and SQL can save you from being overwhelmed with the large amount of data and help you analyze large data sets. 

4. Tableau

A credited platform for analytics and a robust visualization tool, Tableau is an ideal option for interactive analysis and data exploration. With new automation features and upgrades, Tableau lets you approach data analysis in an augmented manner and create vivid and interactive visualizations.

You can play around with graphs, data blending, table calculation, dashboards and much more. Here’s how a Tableau dashboard looks like. Tableau Dashboard

5. Hadoop

It is an open-source software platform that processes and stores huge amount of data across clusters of computing devices. Hadoop is useful in identifying trends and make predictions to enhance decision-making.

A Data Scientist skilled in Hadoop is bound to stand out from the rest because it is one of the most famous big data frameworks. With a surge expected in the Hadoop market, skilled professionals with rich experience in components like Hadoop Distributed File System (HDFS) will be high in demand.

With in-depth technical training in Hadoop features, ecosystem and architectures, a Data Scientist will be able to sail smoothly with parallel data processing and distributed data storage.

6. Spark

Spark is fast gaining popularity as a useful tool for data processing and analysis.

Spark has replaced Hadoop’s YARN and MapReduce as a high performing alternative. It is more productive and glides onto the data to produce desired results.

This is a fast tool for in-memory data processing and offers interactive APIs for efficient streaming of SQL or machine learning workloads that require speedy repetitive access to data. Being skilled in Spark will be an added advantage, together with knowing its counterpart, Hadoop.

7. Statistics

Deep understanding of business statistics is one of the most important skills for a Data Scientist.

What makes you the most sought after candidate in this field?

Statistical skills needed to be a Data Scientist

A thorough knowledge of hypothesis testing, probability and inferential statistics and experience in working with statistical models.

When you use statistics, you will aid the stakeholders in designing and evaluating experiments and taking measured decisions. Skills for a Data Scientist include the need to be acquainted with statistical methods and techniques like maximum likelihood, distributions, estimators, Logistic Regression, Clustering and Linear Regression etc.

8. Mathematics

In order to build your own implementation models, you need to have a strong understanding of the applied mathematical concepts like linear algebra and multivariable calculus.

You will have to face questions related to these concepts during your job hunt for a Data Scientist role. As a Data Scientist, you ought to have a sound judgment on which tests to run and how to decipher its findings. This is possible only when mathematics is your true love. No, this isn’t an exaggeration. Having at least a basic knowledge of calculus and algebra is crucial.

9. Machine Learning

It is quite obvious that as a Data Scientist, you will have to work on data-driven products.

So, master the machine learning concepts. This will save your day when working on machines that make high-value predictions to enable results-driven decisions and intelligent real-time actions, with minimal human supervision.

Algorithm-driven automated environment eases the tasks of Data Scientists as machines analyze extensive data sets. There are automatic sets of generic methods that ease the processes of data extraction and interpretation. The key will be to know when to use which algorithm/technique.

10. Data Munging

As a Data Scientist, never expect to get data that makes sense. You will have to derive meaning from large chunks of data and not be bothered by its inconsistencies and imperfections; recognize the essential and nonessential features in the data and the labels or dependent variables.

To make data speak what you want it to, data munging is the right technique. Munging is cleaning your data to give it a shining look (a structure). Python and R will come to your rescue in this process. So, befriend them.

Behavioral Skills to be a Data Scientist

Lets now move on to some behavioral skills that will benefit you greatly as a Data Scientist.

1. Communication

You need to work on your communication skills to be a Data Scientist. You will have to communicate business reports, data findings, intricate ideas and terminologies to the non-technical business stakeholders.

Communication is the key to establishing fruitful business relationships and strengthening your position as a Data Scientist. This includes both forms of communication- verbal and written.

Imagine a situation wherein, your business applies Random Forest and you have to communicate and convince the reason behind this choice, the process by which this algorithm works, the results it will produce and how will it be beneficial to the business.

This can be too much for a non-technical person, until communication experts like you take up the role of a connecting link.

2. Staying Updated

Being a successful Data Scientist calls for an insatiable appetite for knowledge.

You need to stay updated with the latest trends, happenings, latest technologies, advancements etc. in the field. Learning never stops in the world of Data Science.

Keeping an eye on the development in the vertical/domain other than yours is always advised. The more you stay updated, skilled and learned, the more are the chances of your career advancement.

3. The Right Attitude

The skills for a Data Scientist also include having a zealous attitude and keen intellect towards solving a problem.

You might find yourself dealing with unstructured data and obscure problems with vague indications a lot of the times. Curiosity for how things work and impact each other will be a part of your daily work life. 

4. Sharp Business Intelligence

Because you have to work in a business-driven environment, having an unclogged business understanding is an imperative skill. A Domain Expert is the most-sought after one so gain an understanding of different business-related trends, norms, terms and terminologies.

Having a business acumen and knowledge about how the business works will always help.

5.  Problem Solving

Undoubtedly one of the most important non-technical skills for a Data Scientist, problem-solving helps you in making informed business decisions, driven by data.

It all starts with solving the problem of data cleaning and then moves onto other higher processes. An informed Data Scientist will know the right approach to solve a problem- recognizing the characteristic features of a problem and knowing the right questions to ask. This will help arrive at the solution, judging which are the sensible approximations and contacting the right people.

The more problems you solve, the more experienced you become and advance your career to the next level.

6. Analytical Perspective

Dealing with quantitative and abstract problems, a Data Scientist needs to have an analytical perspective to drive quantifiable solutions.

You will have large datasets to work on, so having a strong and analytical bent of mind will definitely help. The combined skills of mathematics, statistics and programming will aid you in transforming the unstructured datasets and understanding the not so obvious business issues.

7. Storytelling

Besides numerical aptitude, the skills for a Data Scientist also include Storytelling. He knows how to weave words and numbers together and present a story that is easily comprehensible, even by the non-technical folks.

The study thus conducted becomes relevant and has a structure. Developing the right skills for a Data Scientist would also require you to convey the data story to your employers in an engaging way, so it makes sense to them.

Be it numbers, processes or intricate insights, everything will then make sense.

8. The skill to Simplify

Similar to storytelling, this is also one of the prominent skills for a Data Scientist. Intricate insights, reports, data, etc. can be too much for a layman to understand.

If you can break down the complexities and put it forth in a simple way, all the data and the reports will make more sense. Not everyone can understand the results derived from Python or R or Hadoop.

9. Teamwork

Networking, connecting and working with other Data Scientists will help in thinking beyond the scope of just your reports, data and results, etc. Together with this, you will have to work across teams and departments; with product managers to develop better products, with marketing professionals to develop converting campaigns, with software developers to enhance workflow and more.

Needless to say, team members are an imperative part of your daily work schedule. Networking is one of the skills for a Data Scientist that definitely adds to his experience and work profile.

10. The 5W and 1H Questions

A Data Scientist needs to have a questioning attitude; no getting overwhelmed by the huge results from the data. Question why there is something and why something isn’t there at all. Remember the 5W and 1H- Who, What, Why, Where, When and How. Curiosity should be your best friend. Experimentation is the prerequisite to sail through the process of fetching results and insights. Your curious nature will ensure that you hit upon innovative ideas and work for the betterment of your business.

You will be required to have an all-inclusive approach to learn new and improve your existing skills to be a Data Scientist.

In a nutshell, here is an image from LinkedIn that speaks volumes about how important are the skills for a Data Scientist in getting a good job and excelling in it.

Dan Vaughn Importance of Skills for a Data Scientist

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