Whenever we think about data scientists, various complex skill sets come to our mind that is required to perform day-to-day tasks. It is quite common because the role of a data scientist is represented as the fastest-growing and most profitable career path that makes it both complex and competitive. So to help you smoothly pave your way in this journey we provide all the related insights and learning resources. In this blog, we will not only understand the basics of data science but also explore various ways that will push you towards becoming a Data Scientist.
However, you must know that getting into this field will not only provide you a secure career but help you in achieving advancement as well. Another reason is that this field offers you many career paths according to your area of interest.
Let’s start with the basics about data science!
Data Science: Overview
Data science requires deep knowledge discovery through data exploration and inference. This field mainly focuses on using mathematical and algorithmic techniques for solving analytically complex business problems. It includes various core field centers that provide evidence-based analytical accuracy and build strong decision capabilities. However, coming on to the other core of data science is the role of data scientists. So, let’s learn about them.
Understanding the Role of Data Scientist
Data scientist are professional, working and handling a large amount of data and extracting analytical insights. They are excellent communicators who handle processes with stakeholders and drive business growth and profitability. Further, they include various tasks.
- Data scientists work for both business and information technology sectors.
- Secondly, they use their skills to get new data sources and assess their accuracy.
- Thirdly, they simplify and improve the product development, marketing techniques, and business processes by browsing and analyzing the enterprise databases.
- Next, they even create custom data models and algorithms. And, use predictive models for improving customer experience, ad targeting and revenue generation.
- Lastly, they develop the organization’s test model quality and A/B testing framework. And, maintain coordination with various technical/functional teams for implementing models and monitoring results.
However, now we have somewhat understood the importance, basics and roles of the data scientist. But, with great roles comes a lot of competition. That is to say, for getting on top in the data science you need to get familiar and grip on the skills. This will not only help you in getting ahead but also increase your level to get top paying jobs. So, let’s check out the skills essential in this field.
Must have skills for Data Science
- For getting familiarity with R programming, you should have in-depth knowledge of at least one of the analytical tools for data science R. However, R is designed for data science that is used to solve any statistical problems.
You can take help from various resources available to get you started with R.
- There may be some situations in the role of data scientist where the volume of data has exceeded the memory of your system or you need to send data to different servers. This is where Hadoop is required for quickly conveying data to various points on a system. Moreover, you can also use Hadoop for data exploration, data filtration, data sampling and summarization.
- As a data scientist you must be proficient with SQL to access, communicate and work on data. This gives you insights while using it to query a database with concise commands that saves time and reduces the amount of programming. So, learning SQL will help you in understanding relational databases and for boosting your data scientist profile.
- Apache Spark refers to the popular big data technology globally which is designed for data science to run its complicated algorithm faster. Moreover, it helps in handling the complex unstructured data sets. With learning Apache spark, you can carry out analytics from data intake to distributing computing.
Coming on to the trending one!
- Python refers to the most common coding language and is great for data scientists. This can be used for almost all the steps involved in data science processes. Moreover, it can take various formats of data and allows you to create datasets. There are various certification courses out there specifically Data Science with Python that help you get advanced in the same.
Machine Learning and AI
- There are very few data scientists who are proficient in machine learning areas and techniques. So, there is a big chance to earn a better position in the role of data scientist by getting advanced in machine learning. These skills will help you in solving various data science problems based on predictions of major organizational outcomes.
- In the business world, a vast amount of data frequently needs to be translated into a format that will be easy to comprehend. So, having knowledge in data visualization can provide advantage in presenting data in forms of charts and graphs. As people understand more with this rather than raw data. Moreover, with this you must be able to visualize data with the aid of data visualization tools like ggplot, d3.js and Matplottlib, and Tableau.
There are some non-technical skills as well that will provide advantage in this role.
- As a data scientist, it is important that you must have a solid understanding of the industry you’re working in. Moreover, you must understand how the problem you solve can impact the business. That’s why business operation knowledge is important in data science.
- Companies looking for a strong data scientist search for someone who has fluency to translate their technical findings to a non-technical team. You must have the ability to create a storyline around the data for making it easy for anyone to understand. As most business owners don’t want to know what you analyzed, they are interested in how it can impact their business positively.
- A data scientist has to work with different departments like work product managers and designers for developing strategies and creating better products. So, it is important to have the ability to work with everyone in the organization, including your customers.
After understanding the major areas with skills now it’s time to check the important ways that can help in becoming a data scientist.
Whenever we decide to start looking for a career in a certain field, one thing that is taken as priority during research is the salary structure. So, let’s check the salary for the role of a data scientist.
Data Scientists Salary Range
Below are some other top data science roles that you can apply for according to your interest areas.
There are many career opportunities in data that have exponentially grown in the recent few years. Because of this companies are offering high salary packages for data scientists in India. However, the average data scientist’s salary is ₹698,412.
Top Ways and Resources to become Data Scientist
Below we will talk about the essential points and ways that will work as a roadmap to achieve the role of a data scientist.
Do the Research!: Get yourself familiar with Data science concepts
Data science is a field that has both data and code. For this, you will have to develop an analytical mindset and start researching for the in-depth information using the news articles. This will help you understand the area of your interest so that you can immediately start working on it. However, becoming a data scientist is a long road, and this requires passion about the field. So, before moving on to the next step, get a focused mindset about the process of data science.
Start with learning the basics
Once you have understood the basics of data science it times to start picking the technical skills. In this blog, we have talked about various technical as well as non technical skills that you can choose from. However, someone new into this field can start learning about data science with python. to start answering them. As this programming language has consistent syntax, and is often recommended for beginners. For getting understanding of this, there are various tutorials out there which can help you to understand data science with python more accurately.
Or you can take help from reference books. Using reference books can help you get familiarity to gain skills and knowledge in data science. Some of the books related to data science include
- Python Data Science Handbook: Essential Tools for Working with Data Book by Jake VanderPlas
- Doing Data Science: Straight Talk from the Frontline Book by Cathy O’Neil and Rachel Schutt
This can be a beneficial step you can take to enhance your skills level and to make yourself a more marketable candidate. There are various certifications in the data science field that you can choose and prepare for. Moreover, with earning certification you make your CV stronger to get advantage during the hiring process.
Related to this, to get prepared for certification, there are various certification providers out there which help you get prepared with providing expert assistance.
Certification Training Providers
There are various certification bodies that can help you in becoming a data scientist. Out of which, you have to select the certification provider that matches your hopes. The certification providers include,
- Vskills – India’s Largest Certification Body
Assess yourself using Practice Tests
You should assess yourself using practice tests. By doing so, you will be able to learn about their weak areas and can improve them on time. Moreover, it also gives an advantage to improve answering skills to save time during the certification exam. So, get prepared and become certified.
Started building projects
After earning certification, you will have ability and skills to start building projects according to the area you choose. However, you need to remember that building projects will not only help you understand real data science work but you will also get a chance to practice your skills to show to potential employers.
Join communities and share your work
After building some projects, you can share over various communities or sources with many professionals. Doing so, will help you expand your networks and get honest reviews about your work. One advantage of these groups is that these will keep you up to date with the latest trends in data science. Further, you can even work on blogs, in which you can describe your projects and related knowledge.
However, after building an online presence, you can start engaging with other data scientists. As they will provide you knowledge and other important things about data science.
Data science is playing a big role in shaping the workplace of the future. With the use of the latest technologies like artificial intelligence and robotics manual tasks are getting automated. Getting into this field requires hard work as well as certification to enhance your skill level. After gaining the required knowledge start working on projects even on those that require knowledge you don’t have to get yourself advanced. For this, you can take help from various online tutorials for data science. As the demand for data scientists is increasing rapidly with high paying positions.