Top 5 Entry-Level Data Science Jobs: What to Expect in 2024

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Gaurav Roy

08 January 2024

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Top 5 Entry-Level Data Science Jobs: What to Expect in 2024

Explore top 5 entry-level data science jobs before starting your career in Data Science in 2024 and learn about prerequisites and salary insights.

Features

Table of Contents

  • Description

  • Top 5 Entry-Level Data Science Jobs

  • Demand and Job Growth Statistics of Data Science Professionals

  • Reason to Learn Data Science for Beginners in 2024

  • Where to Look for Entry-Level Data Science Jobs?

  • How to Start a Career in Data Science as a Fresher?

  • Top Companies Offering Freshers Jobs For Data Science

  • Best Job Roles to Apply After Pursuing Data Science Courses

  • Data Science Demand In Future

  • In Summary

Explore top 5 entry-level data science jobs before starting your career in Data Science in 2024 and learn about prerequisites and salary insights.

Description

Data Science is one of the most preferred career choices in 2024, and many aspiring individuals don’t know where to start their careers. If you are an aspiring data science professional, you are not alone in the journey with many challenges. Choosing the right entry-level data science job, or even to start your career, can be challenging, but with our list of entry-level Data Science jobs, you will learn about them in-depth and will be able to make an informed decision based on the knowledge.

This article will provide comprehensive details about the top 5 entry-level data science jobs. The article will also highlight the certifications and courses individuals can opt for to get data science jobs roles. Finally, we will also discuss the average salary for each role.

Top 5 Entry-Level Data Science Jobs

You might be wondering what skills and responsibilities are necessary to start a career in data science. This section will help you explore the different data science jobs with their roles and responsibilities. It will also discuss the degree of study you need to land yourself in such roles. Like any career avenue, you cannot land yourself to start as a data science professional.

Let us explore a few necessary data science jobs before getting into a senior role.

 

Junior Data Engineer

Junior data engineers are those who recently graduated from data science courses or plan to make a career switch after completing data analytics courses. As a Junior Data Engineer, you should have hands-on practical exposure to managing data and want to experience real-world scenarios. You will also work under senior data engineers.

 

 

Basic Qualifications

  • Bachelor's degree in Software Engineering, Computer Science, or a related field.
  • Hands-on understanding of data handling.
  • Any certification in data science or data engineering works as a plus point.

 

Roles and Responsibilities

  • Perform the technicalities of collecting, storing, managing, and analyzing data.
  • Develop and maintain the data infrastructure that supports data analysis and modeling.
  • Work on small open-source projects that senior data scientists or engineers pay less attention to. These projects have low priority on the overall business.
  • Create data pipelines, integrate various data sources, and ensure data quality and integrity.

 

Technical Skills

Proficiency in programming languages like Python, R, and Java. Along with programming skills, the knowledge of databases (e.g., SQL, NoSQL) and big data frameworks (e.g., Hadoop, Spark) can be beneficial.

 

Data Analyst Intern

Data analysts are one of the most crucial data science roles in any data-driven firm. As a Data Analyst, you gather, organize, and analyze data to extract actionable insights from granular data. As an intern, you will analyze data extracted from various business sources of the company. 

As a professional in an entry-level tech job, you will rigorously work on sharpening data cleansing skills, generating reports, preparing descriptive analysis, and filtering data necessary for analysis from raw datasets.

Basic Qualifications

  • Bachelor’s degree in Computer Science, Information Technology, Statistics, or Business Management is what most organizations prefer.
  • Any course or certification in data analysis or handling is a plus point.

 

Roles and Responsibilities

  • Deduce conclusions from data.
  • Analyze data and visualization charts from reports.
  • Maintain data systems and data collection.

 

Technical Skills

Data science jobs like junior data analysts or analyst interns must be proficient in programming languages such as Python or R. Also, a solid foundation in Excel, SQL, and data visualization tools like Tableau is essential. professionals with a basic understanding of statistical concepts and interpreting data patterns will stay advantageous in the competitive job market.

 

Business Analyst

Many companies hire business analysts for data science jobs. As a Business Analyst, you are responsible for identifying business problems and using data-driven approaches. 

You will use data points to outline solutions and provide insights from various data points so that business stakeholders can make strategic decision-making from insights. For product- and service-based companies, business analysts prepare forecasting reports and plan budgets according to the market data.

Basic Qualifications

  • Most organizations prefer a Bachelor’s degree in Business Administration, Finance, Economics, Statistics, or Computer Science.
  • Any course or certification in data analysis, business analytics, business data-handling tools, or MS Excel is a plus point.

 

Roles and Responsibilities

  • Analyze business data and generate solutions.
  • Prepare visualizations and other reports for budgets and market predictions.
  • Monitor market conditions and analyze competitors.
  • Analyze the variance.

 

Technical Skills

Data science jobs like business analysts should have strong analytical and problem-solving skills. Other than analytical skills, effective communication, story-telling through data visualization, and stakeholder management abilities are crucial for success in this role. Proficiency in tools like Tableau or Power BI is also beneficial.

 

Entry-Level Database Administrator

Database Administrator is another job in data science in which professionals have to manage, maintain, and secure databases for multiple data systems. This maintenance and management of data can help senior data analysts and data scientists analyze them for business purposes. 

Technically, once you become a Database Administrator, you will handle data storage centers, use SQL and NoSQL commands to manage them and present the data so that data science professionals can use them.

Basic Qualifications

  • Bachelor’s degree in Computer Science is what most organizations prefer. You must have a specialization in database management.
  • Any course or certification in a Database Administrator role, MySQL, NoSQL, etc., is a plus point.

 

Roles and Responsibilities

  • Identify new ways of storing, managing, and organizing data.
  • Update database and database software for other analysts to access them anytime.
  • Design database and schema and work on development.

 

Technical Skills

Entry-level or junior database administrators should have strong analytical and problem-solving skills. Also, proficiency in database management software and database handling programming languages like SQL and NoSQL is a must.

 

Statistician

Statistics is a lucrative domain where professionals can go to multiple entry-level data science jobs. As a statistician in a data science job, you are responsible for mining, collecting, analyzing, and evaluating data to find connections in market trends and relationships between data. 

Statistician also handles data collection process and design, stakeholder communication, and organizational strategy advising. This job is in demand in both the private and public sectors.

Basic Qualifications

  • Bachelor’s degree in Statistics major and Applied Statistics are a plus point. Specialization in IT or data analysis works too.
  • Any course or certification in Data Analytics, Data Mining, etc., is a plus point.

 

Roles and Responsibilities

  • Design the data collection process.
  • Identify patterns and relationships in data.

 

Technical Skills

As a Statistician, you must have a sound understanding of statistical analysis and modeling. Also, statistical software and programming languages like R and Python are necessary for a professional to learn. You should also equip yourself to perform statistical inference and interpretation, data visualization, and statistics data quality control.

You might be wondering what skills and responsibilities are necessary to start a career in data science. This section will help you explore the different data science jobs with their roles and responsibilities. It will also discuss the degree of study you need to land yourself in such roles. Like any career avenue, you cannot land yourself to start as a data science professional.

Let us explore a few necessary data science jobs before getting into a senior role.

 

Junior Data Engineer

Junior data engineers are those who recently graduated from data science courses or plan to make a career switch after completing data analytics courses. As a Junior Data Engineer, you should have hands-on practical exposure to managing data and want to experience real-world scenarios. You will also work under senior data engineers.

 

 

Basic Qualifications

  • Bachelor's degree in Software Engineering, Computer Science, or a related field.
  • Hands-on understanding of data handling.
  • Any certification in data science or data engineering works as a plus point.

 

Roles and Responsibilities

  • Perform the technicalities of collecting, storing, managing, and analyzing data.
  • Develop and maintain the data infrastructure that supports data analysis and modeling.
  • Work on small open-source projects that senior data scientists or engineers pay less attention to. These projects have low priority on the overall business.
  • Create data pipelines, integrate various data sources, and ensure data quality and integrity.

 

Technical Skills

Proficiency in programming languages like Python, R, and Java. Along with programming skills, the knowledge of databases (e.g., SQL, NoSQL) and big data frameworks (e.g., Hadoop, Spark) can be beneficial.

 

Data Analyst Intern

Data analysts are one of the most crucial data science roles in any data-driven firm. As a Data Analyst, you gather, organize, and analyze data to extract actionable insights from granular data. As an intern, you will analyze data extracted from various business sources of the company. 

As a professional in an entry-level tech job, you will rigorously work on sharpening data cleansing skills, generating reports, preparing descriptive analysis, and filtering data necessary for analysis from raw datasets.

Basic Qualifications

  • Bachelor’s degree in Computer Science, Information Technology, Statistics, or Business Management is what most organizations prefer.
  • Any course or certification in data analysis or handling is a plus point.

 

Roles and Responsibilities

  • Deduce conclusions from data.
  • Analyze data and visualization charts from reports.
  • Maintain data systems and data collection.

 

Technical Skills

Data science jobs like junior data analysts or analyst interns must be proficient in programming languages such as Python or R. Also, a solid foundation in Excel, SQL, and data visualization tools like Tableau is essential. professionals with a basic understanding of statistical concepts and interpreting data patterns will stay advantageous in the competitive job market.

 

Business Analyst

Many companies hire business analysts for data science jobs. As a Business Analyst, you are responsible for identifying business problems and using data-driven approaches. 

You will use data points to outline solutions and provide insights from various data points so that business stakeholders can make strategic decision-making from insights. For product- and service-based companies, business analysts prepare forecasting reports and plan budgets according to the market data.

Basic Qualifications

  • Most organizations prefer a Bachelor’s degree in Business Administration, Finance, Economics, Statistics, or Computer Science.
  • Any course or certification in data analysis, business analytics, business data-handling tools, or MS Excel is a plus point.

 

Roles and Responsibilities

  • Analyze business data and generate solutions.
  • Prepare visualizations and other reports for budgets and market predictions.
  • Monitor market conditions and analyze competitors.
  • Analyze the variance.

 

Technical Skills

Data science jobs like business analysts should have strong analytical and problem-solving skills. Other than analytical skills, effective communication, story-telling through data visualization, and stakeholder management abilities are crucial for success in this role. Proficiency in tools like Tableau or Power BI is also beneficial.

 

Entry-Level Database Administrator

Database Administrator is another job in data science in which professionals have to manage, maintain, and secure databases for multiple data systems. This maintenance and management of data can help senior data analysts and data scientists analyze them for business purposes. 

Technically, once you become a Database Administrator, you will handle data storage centers, use SQL and NoSQL commands to manage them and present the data so that data science professionals can use them.

Basic Qualifications

  • Bachelor’s degree in Computer Science is what most organizations prefer. You must have a specialization in database management.
  • Any course or certification in a Database Administrator role, MySQL, NoSQL, etc., is a plus point.

 

Roles and Responsibilities

  • Identify new ways of storing, managing, and organizing data.
  • Update database and database software for other analysts to access them anytime.
  • Design database and schema and work on development.

 

Technical Skills

Entry-level or junior database administrators should have strong analytical and problem-solving skills. Also, proficiency in database management software and database handling programming languages like SQL and NoSQL is a must.

 

Statistician

Statistics is a lucrative domain where professionals can go to multiple entry-level data science jobs. As a statistician in a data science job, you are responsible for mining, collecting, analyzing, and evaluating data to find connections in market trends and relationships between data. 

Statistician also handles data collection process and design, stakeholder communication, and organizational strategy advising. This job is in demand in both the private and public sectors.

Basic Qualifications

  • Bachelor’s degree in Statistics major and Applied Statistics are a plus point. Specialization in IT or data analysis works too.
  • Any course or certification in Data Analytics, Data Mining, etc., is a plus point.

 

Roles and Responsibilities

  • Design the data collection process.
  • Identify patterns and relationships in data.

 

Technical Skills

As a Statistician, you must have a sound understanding of statistical analysis and modeling. Also, statistical software and programming languages like R and Python are necessary for a professional to learn. You should also equip yourself to perform statistical inference and interpretation, data visualization, and statistics data quality control.

Demand and Job Growth Statistics of Data Science Professionals

We all have heard that data is the new oil. Data Science has emerged as a dynamic and rapidly growing field, revolutionizing industries across the globe. Every organization is doing excellent by harnessing the power of data analysis. It helps various firms to stay on top in the competitive market. With data science expanding career opportunities and offering opportunities, including entry-level Data Science jobs, it is clear that the field is in constant growth.

According to the Markets and Markets research report, in 2021, the data science market was $95.3 billion. The report mentions that the data science market will reach $322.9 billion in 2026. It will exhibit a Compound Annual Growth Rate (CAGR) of 27.7% during the forecast period. Data Science professionals like Data Scientists are in demand, and as per the US Bureau of Labor Statistics (BLS), the employment of Data Scientists is expected to increase by 35% by 2032. 

We all have heard that data is the new oil. Data Science has emerged as a dynamic and rapidly growing field, revolutionizing industries across the globe. Every organization is doing excellent by harnessing the power of data analysis. It helps various firms to stay on top in the competitive market. With data science expanding career opportunities and offering opportunities, including entry-level Data Science jobs, it is clear that the field is in constant growth.

According to the Markets and Markets research report, in 2021, the data science market was $95.3 billion. The report mentions that the data science market will reach $322.9 billion in 2026. It will exhibit a Compound Annual Growth Rate (CAGR) of 27.7% during the forecast period. Data Science professionals like Data Scientists are in demand, and as per the US Bureau of Labor Statistics (BLS), the employment of Data Scientists is expected to increase by 35% by 2032. 

Reason to Learn Data Science for Beginners in 2024

In today’s data-driven world, the demand for skilled data science professionals is soaring across industries. The field of data science offers exciting career opportunities and chances to make a difference to the organization and the market drift. 

If you are considering a career switch or seeking to break into the data science industry, learning data science in 2024 can be your game-changing decision. This section will explore notable reasons why beginners should learn data science in 2024.

  • High Demand for Data Science Professionals: The demand for data science professionals is continuous across various organizations. Companies across diverse industries have recognized the importance and potential of data-driven decision-making. By learning data science in 2023, professionals can position themselves in a field with ample job opportunities.
     
  • Lucrative Salary: Data science professionals are among those who get good salaries and salary hikes. Roles like ML engineer and data scientist are top-notch job roles that get hefty salaries for doing excellent projects. So, if any professionals want to pursue a data science career path with attractive salary packages, the time is now. By acquiring different data analytics and data handling skills, professionals can raise their chances of assuring a well-packaged job and enjoying financial stability.
     
  • Myriad Industry-Oriented Applications: Data science and data analysis are not bound to a single industry. It transfuses various verticals, including finance, e-commerce, healthcare, marketing, etc. Professionals who do not want to get bored with one monotonous task can opt for Data Science entry-level jobs. It is a versatile role that allows professionals to explore their interests and apply these analytics techniques in any industry.
     
  • Continuous Learning Opportunities: The field of data science is evolving exponentially. Researchers and engineers are bringing new tools, techniques, and technologies to become precise with predictions and visualizations. Professionals can launch themselves into a continuous learning journey by learning data science. It will help them stay aware and updated with the latest advancements and remain relevant in the industry.
     
  • An Excellent Contribution to Real-World Problems: Data science is ever-evolving. Its new tactics enable professionals to solve complex real-world problems and make informed decisions based on insights fetched from granular data. Whether these professionals deal with predicting customer behavior, developing innovative solutions, or optimizing business processes, data science and data analytics professionals equip the firm to solve real-world challenges.

In today’s data-driven world, the demand for skilled data science professionals is soaring across industries. The field of data science offers exciting career opportunities and chances to make a difference to the organization and the market drift. 

If you are considering a career switch or seeking to break into the data science industry, learning data science in 2024 can be your game-changing decision. This section will explore notable reasons why beginners should learn data science in 2024.

  • High Demand for Data Science Professionals: The demand for data science professionals is continuous across various organizations. Companies across diverse industries have recognized the importance and potential of data-driven decision-making. By learning data science in 2023, professionals can position themselves in a field with ample job opportunities.
     
  • Lucrative Salary: Data science professionals are among those who get good salaries and salary hikes. Roles like ML engineer and data scientist are top-notch job roles that get hefty salaries for doing excellent projects. So, if any professionals want to pursue a data science career path with attractive salary packages, the time is now. By acquiring different data analytics and data handling skills, professionals can raise their chances of assuring a well-packaged job and enjoying financial stability.
     
  • Myriad Industry-Oriented Applications: Data science and data analysis are not bound to a single industry. It transfuses various verticals, including finance, e-commerce, healthcare, marketing, etc. Professionals who do not want to get bored with one monotonous task can opt for Data Science entry-level jobs. It is a versatile role that allows professionals to explore their interests and apply these analytics techniques in any industry.
     
  • Continuous Learning Opportunities: The field of data science is evolving exponentially. Researchers and engineers are bringing new tools, techniques, and technologies to become precise with predictions and visualizations. Professionals can launch themselves into a continuous learning journey by learning data science. It will help them stay aware and updated with the latest advancements and remain relevant in the industry.
     
  • An Excellent Contribution to Real-World Problems: Data science is ever-evolving. Its new tactics enable professionals to solve complex real-world problems and make informed decisions based on insights fetched from granular data. Whether these professionals deal with predicting customer behavior, developing innovative solutions, or optimizing business processes, data science and data analytics professionals equip the firm to solve real-world challenges.

Where to Look for Entry-Level Data Science Jobs?

You can find entry-level Data Science jobs on various platforms online. Here are some of the best ways to find them.

LinkedIn

One of the best places to find entry-level data science jobs is LinkedIn because not only it works as a job board where you can find the latest job postings, but you can also network with your community. 

Networking is one of the best ways to share your interests, and oftentimes, you might land an interview for job postings that are not explicitly posted on the company pages.

Job Boards 

Some other job boards that offer incredible job postings include Monster.com, Glassdoor.com, and Indeed.com. Using these platforms' filters and advanced features, you can specifically look for entry-level positions by adding your experience level and background. You can also look for other preferable options like remote Data Science jobs or specific companies.

Online Communities 

There are some online communities that are specifically related to Data Science job search and hiring. There are other communities that are focused on networking in the data science profession. 

Any of such communities can be fruitful in the long run. You might also get to apply and work for freelance gigs which helps in building your portfolio.

Networking 

Networking is another way to find data science jobs. Having a good online presence on platforms like LinkedIn or Reddit will make networking or building connections easier. 

Apart from online communities, you can also attend conferences and industry events to make your profile/resume more impressionable to potential recruiters.

You can find entry-level Data Science jobs on various platforms online. Here are some of the best ways to find them.

LinkedIn

One of the best places to find entry-level data science jobs is LinkedIn because not only it works as a job board where you can find the latest job postings, but you can also network with your community. 

Networking is one of the best ways to share your interests, and oftentimes, you might land an interview for job postings that are not explicitly posted on the company pages.

Job Boards 

Some other job boards that offer incredible job postings include Monster.com, Glassdoor.com, and Indeed.com. Using these platforms' filters and advanced features, you can specifically look for entry-level positions by adding your experience level and background. You can also look for other preferable options like remote Data Science jobs or specific companies.

Online Communities 

There are some online communities that are specifically related to Data Science job search and hiring. There are other communities that are focused on networking in the data science profession. 

Any of such communities can be fruitful in the long run. You might also get to apply and work for freelance gigs which helps in building your portfolio.

Networking 

Networking is another way to find data science jobs. Having a good online presence on platforms like LinkedIn or Reddit will make networking or building connections easier. 

Apart from online communities, you can also attend conferences and industry events to make your profile/resume more impressionable to potential recruiters.

How to Start a Career in Data Science as a Fresher?

To start a career in data science as a fresher, follow these 5 basic steps.

Get a Bachelor’s degree.

A bachelor’s degree is a common qualification that employers look for in a potential data science professional. It is highly preferable if your degree is in computer science, mathematics or business analysis. If you already do not have a degree in any related fields, you can also pursue a data science boot camp.

Get a certification

There are various data science certifications, but the best data science certifications will come with internships, capstone projects and hands-on experience as features. Getting an industry-recognized certification will help boost your resume, and projects will help you showcase your skills.

Build a Portfolio

Gather your best work in one place to demonstrate your skillset better. Your work doesn’t have to be from a real job since you are still a fresher, but it must show your interest and understanding.

Join communities

You will learn a lot from the communities where you will come across experienced data science professionals and beginners like you who are going through the same journey. One of the best parts of joining a community is they talk about skills, new advancements, and everything in between.

Build your resume and prepare for interviews.

Building a resume is not all about how many skills you have; there are certain tricks to tailor your resume to make potential employers want to hire you. From showcasing your best work to tailoring for specific job posts, learn how to build ATS-friendly resumes from the best and most experienced in the community.

You will also find various resources to prepare for an interview for free.

To start a career in data science as a fresher, follow these 5 basic steps.

Get a Bachelor’s degree.

A bachelor’s degree is a common qualification that employers look for in a potential data science professional. It is highly preferable if your degree is in computer science, mathematics or business analysis. If you already do not have a degree in any related fields, you can also pursue a data science boot camp.

Get a certification

There are various data science certifications, but the best data science certifications will come with internships, capstone projects and hands-on experience as features. Getting an industry-recognized certification will help boost your resume, and projects will help you showcase your skills.

Build a Portfolio

Gather your best work in one place to demonstrate your skillset better. Your work doesn’t have to be from a real job since you are still a fresher, but it must show your interest and understanding.

Join communities

You will learn a lot from the communities where you will come across experienced data science professionals and beginners like you who are going through the same journey. One of the best parts of joining a community is they talk about skills, new advancements, and everything in between.

Build your resume and prepare for interviews.

Building a resume is not all about how many skills you have; there are certain tricks to tailor your resume to make potential employers want to hire you. From showcasing your best work to tailoring for specific job posts, learn how to build ATS-friendly resumes from the best and most experienced in the community.

You will also find various resources to prepare for an interview for free.

Top Companies Offering Freshers Jobs For Data Science

The top companies hiring for freshers jobs in Data Science include:

  • Accenture: Accenture is associated with fields like strategy, consulting, technology, operations, etc., and data scientists. But apart from that, there is a diverse group of Artificial Intelligence(AI) and Data Science teams with diverse roles, and the company welcomes data science freshers.
  • PwC: This renowned global professional services organization stands as a leader among Data Science companies, delivering a diverse array of offerings encompassing assurance, advisory, and tax services. For aspiring data science professionals, a plethora of opportunities awaits within this firm, inviting them to join in revolutionary research and pioneering endeavors.
  • Microsoft: Microsoft is known for its cutting-edge technologies and product offerings and offers an array of employment prospects tailored to data science professionals across various stages of expertise. The organization works on a multiple range of projects and welcomes freshers wholeheartedly.
  • Amazon: This ecommerce platform leverages advantages of machine learning and data science for personalized recommendations for customers and to improve their services to their customers. One of the best places to work for data science professionals as they can enjoy exposure to a wide range of projects.

The top companies hiring for freshers jobs in Data Science include:

  • Accenture: Accenture is associated with fields like strategy, consulting, technology, operations, etc., and data scientists. But apart from that, there is a diverse group of Artificial Intelligence(AI) and Data Science teams with diverse roles, and the company welcomes data science freshers.
  • PwC: This renowned global professional services organization stands as a leader among Data Science companies, delivering a diverse array of offerings encompassing assurance, advisory, and tax services. For aspiring data science professionals, a plethora of opportunities awaits within this firm, inviting them to join in revolutionary research and pioneering endeavors.
  • Microsoft: Microsoft is known for its cutting-edge technologies and product offerings and offers an array of employment prospects tailored to data science professionals across various stages of expertise. The organization works on a multiple range of projects and welcomes freshers wholeheartedly.
  • Amazon: This ecommerce platform leverages advantages of machine learning and data science for personalized recommendations for customers and to improve their services to their customers. One of the best places to work for data science professionals as they can enjoy exposure to a wide range of projects.

Best Job Roles to Apply After Pursuing Data Science Courses

One of the best ways to build data science skills is to enroll in Data Science certifications and crash courses, which play a notable role in furnishing the skillset of an aspirant. This section will explore the various Data Science certifications and online courses available for distinct entry-level data science jobs.

Junior Data Engineer

Junior data engineers are one of the most common data science entry-level jobs. You can become a Junior Data Engineer if you have a background in computer science, information technology, mathematics background, statistics graduate, etc. Here are some of the top courses:

 

Data Analyst Intern 

Data analyst interns are another highly demanding job that leads to a data analyst, then a senior data analyst, and finally to data science roles. You can intern as a Data Analyst if you have a regular graduation with data science certifications, engineering backgrounds, etc.

Here are some courses you need to help you build Data Analyst skills.

 

Business Analyst

Business analysts bridge the gap between technical data teams and business stakeholders. This data science role is well-known in many companies. Such professionals may come from any graduation background – computer science, information technology, mathematics, statistics, management, finance, etc. Here are some of the Business Analyst courses:

 

Entry-Level Database Administrator

Professionals can also move from database domains to data science career options. Various companies hire data science professionals with database management backgrounds. 

It is because companies store and manage data in large databases (structured, semi-structured, and unstructured). Professionals can come from different graduate and postgraduate backgrounds. 

Here are some popular database certifications professionals can go for to start their careers as database administrators.

 

Statistician

As professionals who are statisticians and not directly from a computer science background, you can pursue data science jobs at the entry level. Statisticians have strong data analytical, reasoning, measuring, and estimating power. By upskilling these basic data science skills in different verticals like data mining, data analysis, data visualization, etc., you can land in the data science industry. 

Again, you should possess strong statistical inference and interpretation skills to get a job in entry-level roles. You have to draw meaningful conclusions from data analyses and make data-driven recommendations.

Professionals who are statisticians or have a graduation or post-graduation in statistics can do various certified courses from online learning platforms. There are numerous excellent online self-learning platforms like Careervira. It offers numerous courses on data mining, data analysis, statistics for data science, etc.

One of the best ways to build data science skills is to enroll in Data Science certifications and crash courses, which play a notable role in furnishing the skillset of an aspirant. This section will explore the various Data Science certifications and online courses available for distinct entry-level data science jobs.

Junior Data Engineer

Junior data engineers are one of the most common data science entry-level jobs. You can become a Junior Data Engineer if you have a background in computer science, information technology, mathematics background, statistics graduate, etc. Here are some of the top courses:

 

Data Analyst Intern 

Data analyst interns are another highly demanding job that leads to a data analyst, then a senior data analyst, and finally to data science roles. You can intern as a Data Analyst if you have a regular graduation with data science certifications, engineering backgrounds, etc.

Here are some courses you need to help you build Data Analyst skills.

 

Business Analyst

Business analysts bridge the gap between technical data teams and business stakeholders. This data science role is well-known in many companies. Such professionals may come from any graduation background – computer science, information technology, mathematics, statistics, management, finance, etc. Here are some of the Business Analyst courses:

 

Entry-Level Database Administrator

Professionals can also move from database domains to data science career options. Various companies hire data science professionals with database management backgrounds. 

It is because companies store and manage data in large databases (structured, semi-structured, and unstructured). Professionals can come from different graduate and postgraduate backgrounds. 

Here are some popular database certifications professionals can go for to start their careers as database administrators.

 

Statistician

As professionals who are statisticians and not directly from a computer science background, you can pursue data science jobs at the entry level. Statisticians have strong data analytical, reasoning, measuring, and estimating power. By upskilling these basic data science skills in different verticals like data mining, data analysis, data visualization, etc., you can land in the data science industry. 

Again, you should possess strong statistical inference and interpretation skills to get a job in entry-level roles. You have to draw meaningful conclusions from data analyses and make data-driven recommendations.

Professionals who are statisticians or have a graduation or post-graduation in statistics can do various certified courses from online learning platforms. There are numerous excellent online self-learning platforms like Careervira. It offers numerous courses on data mining, data analysis, statistics for data science, etc.

Data Science Demand In Future

Every company is becoming a data-driven decision-making company. Even researchers are exploring new techniques, frameworks, and tools to enhance the different branches of data science. The field of data science will continue to evolve and develop in multiple areas. 

Machine learning algorithms will continue to enhance. It will be able to accurately and efficiently analyze data. Enterprises will encounter more efficient advanced deep learning algorithms like reinforcement and transfer learning.

Real-time data analysis and statistical inferences will become quicker because of the more powerful computing systems that would leverage Graphical Processing Units (GPUs) and Tensor Processing Units (TPUs).

Since the data science implementation and research market is booming and growing exponentially, professionals who want to build their careers in this vertical will have maximum advantage. The salary package will also increase, and unlocking new business possibilities through data will make this data science domain flourish.

Every company is becoming a data-driven decision-making company. Even researchers are exploring new techniques, frameworks, and tools to enhance the different branches of data science. The field of data science will continue to evolve and develop in multiple areas. 

Machine learning algorithms will continue to enhance. It will be able to accurately and efficiently analyze data. Enterprises will encounter more efficient advanced deep learning algorithms like reinforcement and transfer learning.

Real-time data analysis and statistical inferences will become quicker because of the more powerful computing systems that would leverage Graphical Processing Units (GPUs) and Tensor Processing Units (TPUs).

Since the data science implementation and research market is booming and growing exponentially, professionals who want to build their careers in this vertical will have maximum advantage. The salary package will also increase, and unlocking new business possibilities through data will make this data science domain flourish.

In Summary

We hope this article has shown clear detail about the top 5 entry-level jobs in data science. The article also highlighted reasons professionals should learn data science and build a career in this vertical. Then, we presented details about the top 5 data science jobs, along with their required qualifications, roles, technical skills, and salary slabs.

If you want to upskill yourself and join any entry-level data science job role as a career, it is time to learn the latest along with basic Data Science skills. Careervira is an excellent platform that offers data science courses.

We hope this article has shown clear detail about the top 5 entry-level jobs in data science. The article also highlighted reasons professionals should learn data science and build a career in this vertical. Then, we presented details about the top 5 data science jobs, along with their required qualifications, roles, technical skills, and salary slabs.

If you want to upskill yourself and join any entry-level data science job role as a career, it is time to learn the latest along with basic Data Science skills. Careervira is an excellent platform that offers data science courses.

Features

Table of Contents

  • Description

  • Top 5 Entry-Level Data Science Jobs

  • Demand and Job Growth Statistics of Data Science Professionals

  • Reason to Learn Data Science for Beginners in 2024

  • Where to Look for Entry-Level Data Science Jobs?

  • How to Start a Career in Data Science as a Fresher?

  • Top Companies Offering Freshers Jobs For Data Science

  • Best Job Roles to Apply After Pursuing Data Science Courses

  • Data Science Demand In Future

  • In Summary