A projected rise of 31.4% by 2030 places being a data scientist among the top 10 fastest-expanding professions in the U.S., according to the U.S. Bureau of Labor Statistics. There has never been a better moment to enter the area of data science, with a median pay of $131,490.
However, switching careers is not something that can be accomplished quickly. Before they are prepared for their first day on the job, aspiring data scientists must complete a number of processes, from education and portfolio development to networking and interviews.
The amount of work that has to be done is undeniable, but it doesn’t have to be intimidating. With the help of our 9-step method, you’ll be able to set up and visualize specific objectives that will enable you to advance toward your first position in the data science industry. If you’re prepared to work towards getting your dream career, continue reading!
What Is the Role of a Data Scientist?
A technological specialist specializing in data collection, management, manipulation, and analysis is known as a data scientist. In all their forms, data scientists attempt to comprehend the data they deal with and then use it to exhibit or forecast valuable and profitable insights. They frequently have computer science, mathematics, statistics, and business backgrounds.
What Do Data Scientists Actually Do?
Data scientists spend a lot of their time gathering and preparing data since they regularly work with enormously massive data sets, or “big data.”
A data scientist may next evaluate this data to derive useful business insights, feed it to an AI or machine learning project and create new tools to simplify the data wrangling process; depending on the specifics of the function, you can either process it or store and organize it in a database.
Common Positions in Data Science:
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Data Scientist
A broad position with the following possible duties:
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Collecting and managing big data sets
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Developing software and algorithms to aid in automating the data-wrangling process
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Using EDA to analyze data (exploratory data analysis)
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Using visualization to make data so that everyone can understand the insights obtained
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Data Analyst
A position can be found in various sectors, including technology, healthcare, entertainment, and finance. Among the responsibilities are:
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Receiving questions and requests for information from stakeholders and decision-makers at the company
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Gathering pertinent data and organizing it in relational databases so that it is ready for searching and analysis
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Using the data, identifying valuable insights, and demonstrating them for simplicity
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Presenting the results and findings to the relevant employees of the firm. You can also become a data analyst with the best data analytics course, offered by Learnbay.
9 Steps to Becoming a Data Scientist:
How to genuinely become a data scientist is as follows:
Step 1 – Learn Data Science Foundations:
Starting off easy is never a waste of time because niches and specialties cannot be worked on until the fundamentals of the profession have been mastered. You should focus your emphasis on the following:
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Statistical analysis: This describes the use of statistics to analyze data and present the findings in an accurate and unbiased manner.
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Programming: Writing code and developing software are essential skills in many branches of data science.
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Data Visualization: Data is presented in tables, graphs, charts, and dashboards so that both technical and non-technical people may quickly and easily understand it.
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Machine Learning: Constructing computer software that “learns” from the information it provides and uses that information to alter its operations in response to various circumstances nimbly.
Step 2 – Obtain the required education:
Although a college degree is not necessary to become a data scientist, there are frequently some educational prerequisites you need to be aware of before you try to secure your first position.
Although a bachelor’s degree is not necessary for working in data science, it can be beneficial.
College programs incorporating parts of mathematics, computer science, statistics, and business science are known as data science degrees. As a result, a data scientist can qualify with a distinct or advanced degree in any of these or other pertinent subjects.
If you don’t have a college degree or don’t want to get one, there are several ways to enter the data science community. A certification course or enrollment in a data science boot camp are excellent ways to receive an in-depth, hands-on education in the subject of data science and, specifically, the job of a data scientist. Also, check out the data science course fees offered by Learnbay.
Step 3 – Plan your specialization and career path:
Once you have the fundamentals down, it is incredibly beneficial. It will offer you an advantage in the job market to start charting your course and developing a niche or specialization.
Step 4 – Develop Crucial Skills:
An excellent way to show off your skills is by obtaining data science certifications or creating your own projects to highlight the following abilities. Since IT employees work with computers on a daily basis and might save time and effort if they knew how to troubleshoot issues on their own, general technical skills are valuable to them.
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Computer Languages
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Data mining
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Data visualization
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Statistics
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Data Analysis
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Machine Learning
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In-depth Learning
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Algorithms
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Natural Language Processing (NLP)
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Data Engineering
Step 5 – Learn About the Main Data Science Tools:
Here is a list of common data science tools so that you can become acquainted with them.
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Apache Spark: A machine learning and analytics engine for big data processing and engineering
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Tableau: A database-connected tool for data visualization that enables users to design robust and diverse visual representations of their data.
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SAS: A collection of statistical software tools for managing, analyzing, forecasting, and visualizing data.
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MATLAB: A programming language for building models and developing algorithms.
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Python: 75% of data scientists usually use the readability-focused programming language Python.
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R: A programming language for statistics that 47% of data scientists utilize.
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BigMl: A well-liked platform for machine learning.
Step 6 – Create a portfolio and engage in projects to gain real-world experience:
If you lack official schooling or experience, building a sizable, impressive, and high-effort portfolio is a terrific way to demonstrate your talent and dedication. Since individuality and creativity are highly regarded, no two portfolios must be identical, and you can select any data science projects that catch your attention.
Step 5 – Build a Network:
Building your network is a great way to get your foot in the door when you first enter a field. It will help you develop your skills, make new friends with similar interests, work on passion projects, and finally find employment.
Step 6 – Pursue an internship in data science:
If you are fortunate enough to work for no money or a pitiful rate, consider applying for a data science internship to augment your studies with real-world experience.
Step 7 – Prepare for and succeed in the data science interview:
Research is essential while getting ready for a data science interview. Do some research on the business, the people, the position, common data science interview questions, and suggested interviewer questions.
Last Words:
Hope you gained some insights for your data science career journey. The initial steps in learning data science are understanding and dealing with the key technology frameworks used for large data analysis. You will learn how to apply complex data science techniques, the main statistical language, R, and the development and programming frameworks Hadoop and Spark, both used to process massive amounts of data in a distributed computing environment. The insights you will discover from the data are presented as easily readable reports using visualization tools like Tableau. Learnbay’s data science course with placement proves that you have made significant progress in domain mastery. Working on projects, participating in contests, and reading case studies will provide you with the knowledge and skills you need to succeed.
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