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How to Build a Successful Career in Data Science - A Complete Data Science Career Guide

Introduction

Are you among the one who is fascinated by the word Big data? Do you wonder why organizations and businesses showing interest to hire data science professionals in recent years to handle this big data? Well, today’s world is data-driven, you can also say data loaded. Statista predicts that the amount of data generated globally will surpass 180 zettabytes by 2025, up from 64.2 zettabytes in 2023. Therefore, there is no surprise that the demand for skilled data science professionals is towering.

If you are an aspiring data science professional or you want to advance your career in this revolutionary sector, this data science career guide will provide you with all the information you need to know. You will know about the tools that you have to master, the skills you have to develop, and the path you have to choose to embark on your career in this fascinating field. In addition to this, you will also know how the data science certification courses help you undergo practical learning and increase your job market value. 

 Also, Let’s explore how technical skills and soft skills are combined together in data science and how data science professionals use these skills and tools for the success of the organization.

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Data Science - An Overview

Data science is a technology used by start-ups to lead MNCs in extracting insights from data by combining the fields of mathematics, statistics, and computer programming. In this data-driven world where every piece of information is data, right from social media posts to articles data science plays an inevitable role to convert structured or unstructured data into meaningful and processed data. 

The applications of data science are demanded in every field like E-commerce, health, business, finance, administration, and much more. Around 80% of businesses worldwide Invest a significant portion of their profits in building out a capable data analytics division, hiring the most knowledgeable individuals in the field.

Who is a Data Scientist?

In today’s world of big data, organizations use data scientists to handle vast amounts of data. Data scientists are professionals with high analytical skills, programming skills, and decision-making skills. They fetch information or data from various sources, manage them, and provide solutions for complex problems. Using machine learning techniques and tools such as Python  can improve the quality of the data. Here, you can go through a thorough data science road map which assist you in moving up the Data Science career path.

Skills Required To Excel Data Science Career

According to estimates, the market for data science platforms will increase at a compound annual growth rate (CAGR) of 27.7% from USD 95.3 billion in 2021 to USD 322.9 billion in 2026. Therefore, getting the required skill set and knowledge will pave the way for a promising career as the data science market grows rapidly. In this section of the data science career guide, we will see what are data science skills required by an individual to meet the requirements required in this competitive field.

Excel Data Science Career

Programming knowledge

One of the most required data science skills for every data science professional is  programming language. R or Python is the programming language used by data scientists for analyzing and managing large volumes of data. Mastering programming languages helps you in building a successful data science career. R, C, C++, Shell Scripting & SQL are some of the languages you have to learn with sound knowledge of Python.

Machine Learning

In your data science career path, expertizing in machine learning is vital as it helps you to manage and analyze data more efficiently. Linear regression, logistic regression, random forest algorithm, and Raive Bayes are some of the machine learning algorithms. Having an exceptional knowledge of machine learning algorithms helps you to synthesize data effectively and come up with data outcomes for future prediction.

Deep Learning

Deep learning is advanced machine learning, which layers the algorithms and computing units and creates an artificial neuron network that resembles the human brain. Therefore, deep learning doesn’t more human intervention like machine learning and learns independently from the environment and prior errors. Data scientist can benefits from deep learning techniques in analysing and processing huge datasets.

Communication Skills

In the field of data science, communication plays a vital role. To communicate your insights, analyses, and findings with the professionals in your organization or with the people who may not know much about the technical aspects of the field effective communication is necessary. By getting feedback from the audiences you can develop an interaction with them which in turn helps you to improve your communication and creates a successful data science career path.

Statistics

For building a successful data science career, having statistical knowledge is essentially important. Wonder why? Statistics is completely based on facts and not on guesses similar to mathematics. For problem-solving and decision making particularly in data science, you need to think critically. This doesn’t mean you have to get a doctorate in statistics, but having a basic understanding helps you to get deeper data insights.

Data Manipulation

Just think about your school attendance register where all names are written in alphabetical order, so that you can get the information easily. Similarly, data manipulation using R is a method to organize data and keep it structured to access information easily. It is an essential component in business organization since structured data is crucial to study customer behavior, knowing the trend, and improving productivity.

Data Science Career Guide- Roles and Opportunities in Data Science

The roles and  opportunities for data science professionals increase with the need of processing and analyze data in organizations and businesses in order to handle the enormous set of data. Data mining, data visualization, and data storage have to be done while handling the data for which various roles are assigned to data professionals.

Roles and Opportunities in Data Science

Data Analyst

With many data-based jobs available the role of the data analyst is considered to be unique. It is considered to be an entry-level job in the field of data science. As a data analyst, you are responsible for gathering data through surveys, tools, or software. The information you interpret from this data is ideal for making critical decisions for an organization. To perform efficiently and effectively, data analysts should have strong mathematical, technical, and analytical skills.

Business Intelligence Analyst

If you have a passion for the data field and also want to play a major part in the growth of a company, the role of business intelligence analyst suits you better. Also, the demand for the same is growing day by day. According to Indeed, the average annual salary of a business intelligence analyst is $85,535. Data mining and visualization, marketing analysis, and machine learning are some of the skills your expertise as a business intelligence analyst.

Data Architect

An IT professional who is responsible to design and create the data architecture for storing and managing the data of an organization. Using computer knowledge and design skills you will create a blueprint of the data framework. This integrated blueprint requires managing the data and making it easily accessible to meet the requirements of businesses and organizations.

Data Scientist

Data scientists are data experts who play a major role in uncovering business trends, finding the risk and opportunities in business using technical skills. The conversion of raw data into easily understandable one, recognizing the patterns in the data, and data visualization are some of your key responsibilities as a data scientist. According to the U.S. Bureau of Labor Statistics, the projected percentage growth of employment in data science is estimated as 36%, which is higher than the average of all other occupations.

Senior Data Scientist

As a senior data scientist you will have the capability to predict the future needs of your organization. In addition to gathering data, you discover insights to effectively address extremely complicated business challenges. As an experienced professional, you are also able to create new applications for statistical data and construct tools to aid in further data analysis.

Data Manager

The key responsibility of a data manager is organizing, storing, optimizing, and analyzing the organization’s data.  You should ensure that all the processes should be done with utmost security and confidentiality. You should be able to analyze and interpret the vast amount of data. The duties of a data manager include formulating policies, diagnosing issues with database management systems, and guaranteeing the security of data flow to and from the company.

Data Scientist Career Outlook

With the right qualifications and skills, you can grasp plenty of opportunities in the data science field. Either a fresher who dreams of getting a job in data science or an employee who is already working in this growing field is sure to get an attractive salary and reach a higher hierarchy in the future with proper learning in data science. 

According to World Data Science Initiative, a data scientist earns an average salary of USD 176,213 and a data engineer earns an average salary of USD 166,992 in the field of data science and machine learning. The US Bureau of Labor Statistics states that data scientists are expected to have an average of 13,500 job opportunities every year.

The above facts are just a few examples. The future of data science is huge and it will revolutionize and innovate the data-driven world.

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Tools Used in Data Science

Data science tools are the software or applications which is used by data science professionals for cleaning, mining, and analyzing unstructured or structured data. This section of the data science career guide will help you explore the tools used in data science education. The following is the list of the most in-demand data science tools.

  • Apache Hadoop
  • Tableau
  • TensorFlow
  • Statistical Analysis System (SAS)
  • MongoDB
  • Rapidminer
  • R Programming

Data science professionals work on multiple data science tools for data analysis, data mining, and data visualization. Based on specific preferences, data science professionals employ these tools to carry out data processing.

Data Science - Industry Update

This portion of the data science career guide explains to you how the field of data science is opening up for different job opportunities and growing at a fast pace across other fields.

The market for worldwide data science platforms, which was valued at $4.7 billion in 2020, is expected to increase at a CAGR of 33.6% from 2021 to 2030, reaching $79.7 billion.

Prerequisites for Building a Successful Data Science Career

As a data science professional you are going to handle a massive volume of data. The data science career roadmap requires certain educational requirements which makes your entry into this field easier. These requirements include data science, finance, business studies, statistics, and mathematics. Several data science certifications courses are available both online and offline. You can join those data science classes and acquire the relevant skill set in the process of building a successful data science career.

According to the US Bureau of Labor Statistics, while having a bachelor's degree is the minimum required, most employers offer preference to applicants with higher qualifications, preferably a master's degree. Hence, many data science professionals are taking up data science training and getting data science certificates to keep them forward and updated in the latest technologies and tools.

Along with the educational qualification, technical skills like programming, artificial intelligence, machine learning, etc., are also important prerequisites in the data science career path. Moreover, interpersonal communication, decision-making, teamwork, and curiosity are some of the qualifications you need to possess to succeed in the field of data science.

Final Thoughts

Hope I have shared some useful insights about the data science field and sowed some ideas about the data science career path through this article, data science career guide. Since the requirement of data science technology is growing day by day there are endless opportunities and growth possibilities for the individuals whose has excellent data science skills.

Embrace the power of learning throughout your life and keep yourself updated with the latest trends and technologies. Also, remember to build a successful data science career, along with acquiring knowledge in technical and educational aspects, and have a passion for data science. To explore various opportunities and get professional training, Data Science Courses at JanBask help you to master the field and enhance your career growth. Enrol now to land your dream job.

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FAQs

Q.1 How online data science course helps to achieve a successful career in data science?

Ans:- Online data science courses can offer several benefits for your career. As there is a massive demand for data science professionals, data science education online provides you with the opportunity to learn data science skills like programming, machine learning, etc., Online data science training courses are offered by various institutes, and the options for choosing flexible timings, EMI, one on one guidance gives you the best opportunity to learn breaking the barriers of any kind.

Q.2 What is the best Data science career advice one can give for building a successful career in the field?

Ans:- Data science is a broad field with various opportunities and roles. You should be precise about what kind of role you are ambitious and interested in. After finding which domain suits you the best develop and upgrade your skills in that particular domain. Data science training by means of certification courses helps your possibility to enhance your data science job prospects. Building a strong portfolio and a thirst for learning and updating helps in the professional development of the data science career path.

Q.3  What are the essential data science skills required to enhance data science job prospects?

Ans:- Following are some of the skills a data science professional should be well-versed in since the field of data science is a combination of statistics, programming, analysis, and much more.

  • Programming skills
  • Statistics
  • Machine learning
  • Communication skills
  • Knowledge of big data tools and more.

Q.4 List out the areas where data science is commonly used.

Ans:- Data is the key component in every field whether it is the health industry or business. Hence to process and analyze data, the implementation of data science skills is mandatory. 

  • E-commerce
  • Business and Finance
  • Marketing and Advertising
  • Health department
  • Telecommunication
  • Transportation
  • Weather forecasting and in many fields, data science plays a vital role.

Q. 5  Name some best data science courses.

Ans:- Following are some of the best Data Science certificate courses.

  • Deep learning
  • Tableau
  • Data Science with R
  • Data Visualization
  • Data Engineering
  • Python Development-Master


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