How to Get a Job in Data Analytics? [Steps, Tops Roles, Tips, & More]

The Indian market for big data analytics is expected to reach $16 billion by 2025, which is a clear indication of the enormous growth in this area. However, the question is whether data analytics is a promising career. According to a recent study, data analytics is one of the most in-demand skills in various industries. Companies are investing in data analytics to increase the efficiency and scalability of their businesses, increasing the demand for skilled experts. In this blog, we will explore how to get a job in data analytics, reasons to pursue this career, top roles to apply for, and useful tips to secure your dream data analytics job.

Why Pursue a Career in Data Analytics?

Before exploring how to secure a data analyst job, it’s important to understand why you should pursue a career in this field. Today, a massive amount of data is created, making data-driven insights an asset for organizations. Businesses seek professionals who can analyze data, extract meaningful insights, and derive relevant solutions for existing and emerging business problems. However, the increasing demand for experts is one of many reasons why data analytics has emerged as one of the most popular careers. 

Here are some more reasons to choose a career in data analytics:

• High Remuneration: The data analytics industry offers competitive remuneration, often depending on location, experience, and industry. The average highest salary of data analysts in India is ₹14.4 LPA.
• Challenging and Exciting Work: Data analysts often delve into large datasets, uncovering valuable insights that make the work exciting and intellectually stimulating. If you like solving complex problems and want to make an impact through data-driven decisions, this career is the ideal option.
• Opportunities in Diverse Industries: Data analytics is used in several industries, including healthcare, e-commerce, retail, manufacturing, and banking. This ensures diverse job opportunities for individuals who want to pursue a job in this field.
• Transferable Skills: As a data analyst, you can develop vital skills that will help you in the future if you decide to explore or change careers. These skills include data management, statistical analysis, data visualization, etc. 
• Future-Proof Career: The number of jobs for data analysts is expected to increase by 23% between 2021 and 2031, highlighting a positive global trend. So, if you are looking to build a future-proof career, consider applying for data analytics or big data jobs.

How to Get a Job in Data Analytics?

To begin working in the data analytics industry, you should follow a roadmap that provides steps from gaining the necessary education to applying for fresher jobs. Here’s a useful roadmap that you can check out to learn how to get a job in data analytics:

1. Obtain Necessary Qualifications

Start by obtaining the necessary education relevant to data analytics. A bachelor’s degree is required to apply for data analyst jobs. You should acquire a degree in subjects that focus on statistical and analytical skills. Here are some of the courses that you can pursue in graduation and post-graduate studies:

• B.Tech. in Information Technology
• B.Tech./B.Sc. in Computer Science
• B.Sc. Statistics
• B.Sc. Mathematics
• B.Sc. Economics

If you are seeking opportunities with lucrative pay, consider pursuing a master’s or a doctoral degree in a similar field. Further, if you possess a bachelor’s or higher degree in some other field, you still pursue a career in data analytics. Consider enrolling in a data science course with a placement offer to acquire the skills, learn to work on data analytical tools, and apply for jobs upon completion of the course. 

2. Develop Essential Data Analytics Skills

To understand how to get a data analytics job, you should be familiar with the essential skills required for the job. Here are some of the crucial skills required to work as a data analyst:

i. Familiarize Yourself With the Basics of Data Analytics

The first step towards developing skills in any domain is to familiarize yourself with its basics. You should know about the basic concepts in data analytics related to data, mathematics, statistics, etc. Here are some essential fundamentals to remember:

• Data types (such as text, numerical, and categorical) 
• Data collection methods (like weblogs, sensors, surveys, etc.)
• Common data challenges (like outliers and missing values)
• Mathematical and statistical concepts (like algebra, probability, calculus, etc.)

ii. Learn a Programming Language

Next, learn a programming language commonly used in data analytics, such as R, Python, and SQL. These languages will help you manipulate data, analyze it, and create data visualizations. 

• R is widely used in statistical analysis, data visualization, and academic research. It is useful in handling complex statistical computations.
• Python is a programming language used in data analytics for its simplicity and extensive libraries like matplotlib, pandas, and NumPy. It is preferred for data manipulation and automation tasks.
• Structured Query Language (SQL) is used to manage and query relational databases. It is crucial for data extraction, transformation, and loading (ETL) processes in data analytics. 

iii. Master Data Cleaning and Data Wrangling

Your dataset may contain both structured and unstructured data. Therefore, data cleaning and wrangling processes are performed to clean and transform data into a usable format. In this process, errors, inaccuracies, and inconsistencies are identified and corrected in the datasets. 

This data is converted into a format that is legible for analysis. You may have to reshape, aggregate, or enrich the data to transform it. Finally, all the data collected from diverse sources is presented as one dataset through data integration.

iv. Master Statistical Analysis

Statistical analysis is imperative to data analytics. It is the process of gathering and analyzing large amounts of data to identify trends and infer valuable insights. To excel in the data analytics field, you should master the following statistical techniques:

• Regression Analysis: This method is used to understand the relationships between a dependent variable and one or more independent variables.
• Inferential Statistics: This technique helps you draw inferences about a population based on a sample.
• Hypothesis Testing: This systematic procedure helps decide whether the results of a study support a particular theory or hypothesis that applies to a population.
• Descriptive Statistics: This refers to a set of methods that summarize the main features of a dataset, like its distribution and variability.

v. Acquire Proficiency in Data Analytics Tools

You will use a range of tools when working as a data analyst. This guide on how to get hired as a data analyst discusses the data analytics tools that you should learn. Some of these tools include the following:

• Microsoft Excel: It is a spreadsheet application that provides data organization, analysis, and visualization capabilities. Data analysts prefer to use Excel because of its ease of use, advanced features like pivot tables, and built-in functions for statistical analysis.
• Tableau: It is a powerful data visualization tool that allows users to create interactive and shareable dashboards. You can transform raw data into structured format with Tableau’s intuitive drag-and-drop interface.
• Apache Spark: It is an open-source unified analytics engine for large-scale data processing. You get high-speed processing and in-memory computing capabilities with Apache Spark.
• Google Analytics: It is a web-based analytics platform. With Google Analytics, you can monitor website traffic and gain valuable insights.

vi. Develop Soft Skills

Attention to detail, effective communication, and the ability to solve complex problems are qualities needed for working in the data analytics field. Let us discuss them here:

• Attention to Detail: Even a small error can lead to incorrect results in data analytics, making attention to detail highly crucial. It is essential for ensuring the accuracy of data and quality assurance.
• Communication Skills: You should work on your ability to weave data into a compelling narrative that drives business decisions. You should be able to translate data into actionable insights that non-technical stakeholders can easily understand.
• Problem-Solving: To get a job in data analytics, problem-solving skills like critical thinking, analytical reasoning, and thinking outside the box are essential. These abilities help you to evaluate issues objectively. 

3. Practice Your Technical Skills

It is crucial to practice and improve your capabilities to apply for a data analytics job. Here are some ways to hone technical skills relevant to data analytics:

i. Projects

If you are a candidate wondering how to get a data analyst job with no experience, you can start your professional journey by working on projects. This can help you practice technical knowledge as well as prepare samples to showcase your expertise to a prospective employer. You can choose to work on open-source projects that target a real-life problem. 

Remember to use platforms like GitHub to track changes and for version control. Additionally, you can use platforms like Kaggle, DataLab, Google Dataset Search, etc., to access free datasets for your data analytics projects.

ii. Internships

If you are wondering how to get a data analyst job without experience, begin exploring internship opportunities. You can download job search apps like Internshala and find data analytics internships. These internships provide you with relevant work experience and make you eligible for job opportunities that seek experienced professionals. 

iii. Certification Programs

You can enroll in online certification courses with assignments and project work in their curriculum. Working on these assignments will allow you to practice and receive feedback from mentors associated with the programs. This will help you improve your skills tremendously. Some of the courses you can pursue include: 

• SQL for Data Analytics Course
• Data Structures & Algorithms Course
• Statistics for Data Science Course

4. Build a Resume and Portfolio

An essential step in the process of how to land a data analyst job is drafting a professional data analyst resume and building an impressive portfolio. You can check and use specific resume formats to ensure that you present a concise and clear document that passes through the applicant tracking system (ATS). Do customize it to highlight your expertise, recent accomplishments, and experience. 

Those with no or less experience can mention their projects, workshops, training programs, internships, or similar details. Many employers ask for cover letters along with resumes. You can check out how to write an effective data analyst cover letter to make a strong impression on hiring managers.

When preparing a portfolio, keep in mind the following details:

• Mention your full name, contact information, and link to the online portfolio, if any.
• Provide details about the project, like collaborators, date, duration, topic, methodology, tools, results, and any other significant information.
• Place the projects in chronological order in the portfolio. 
• Do mention if any of the projects won a competition or had other achievements.

5. Apply for Entry-Level Jobs in Data Analytics

Recent graduates may want to know how to get an entry-level data analyst job right after college. There are several ways to find and apply for fresher jobs in data analytics, including the following:

• Engage in Placement Drives: Participate in university or college placement drives. This allows you to practice your interview skills as you interview with multiple companies. 
• Download Job Search Apps: Sign up on a job app or website like Internshala, Indeed, Nuakri.com, etc.
• Attend Job Fairs: You will find company representatives and recruiting professionals there who will guide you on how to get a data analyst job as a fresher in their company.
• Check a Company’s Career Page: Visit companies’ official career websites to check the latest open vacancies as per your preferred profile and location.
• Leverage Social Media Platforms: You can search for data analytics jobs through social media platforms. Several employers post about the latest openings in their organization on their social media pages. 

6. Prepare for Interview

The interview round is typically the last in the recruitment process. Employers prefer this face-to-face interaction to gauge your skills and knowledge. You can enhance your chances of securing a data analyst position by thoroughly preparing for the interview. 

Here are some sample data analyst interview questions asked in a data analytics interview:

• What is data cleaning?
• Why is the pivot table used?
• Mention some of the tools used in data analytics.
• What is the K algorithm?
• Explain collaborative filtering.
• Tell us how you will optimize a model in a real-time streaming data application.

Top 5 Entry-Level Job Roles in Data Analytics [With Salaries]

We have discussed in detail how to find a data analyst job. Now, let us also explore some of the top entry-level job roles in the domain. Here are some of the popular and lucrative fresher opportunities available in data analytics:

i. Junior Data Analyst

These professionals work under experienced analysts on data analytics projects. They collect and analyze data to provide insights into customers, industry trends, and market conditions. Junior data analysts also assist in the preparation of reports based on the collected data and interpretations. 

Average Salary: ₹5 LPA to ₹10 LPA

ii. Operations Analyst

Operations analysts evaluate various operational procedures in a business and provide actionable recommendations. The specific duties may differ depending on the industry they are working in as an operations analyst. For example, in the insurance sector, operations analysts may study customer onboarding methods and suggest ways to streamline these techniques. 

Average Salary: ₹5 LPA to ₹9 LPA

iii. Junior Quantitative Analyst

These experts use quantitative techniques to assist companies in making business and financial decisions. Quantitative analysts are hired by investment banks, insurance companies, private equity firms, etc., to identify profitable investment opportunities and manage risk. 

Average Salary: ₹6 LPA to ₹12 LPA

iv. Junior Financial Analyst

Financial analysts advise companies on financial matters like investing in stocks and bonds. They investigate and determine the potential return on investments and suggest how to maximize financial performance. These professionals assist experienced financial analysts in developing financial models and conducting analysis. 

Average Salary: ₹4 LPA to ₹9 LPA

v. Business Analyst

An entry-level business analyst helps in determining the requirements of the company and recommends relevant information technology (IT) resources to strengthen business processes, increase sales, and improve efficiency. They may also help senior business analysts monitor the IT team in an organization. 

Average Salary: ₹6 LPA to ₹12 LPA

Tips to Get a Data Analyst Job

To understand how to get a job as a data analyst in India, read the following useful tips that can help you fast-track the process of securing a job in data analytics:

1. Expand Your Network: Connect with other data analytics professionals on platforms like GitHub and LinkedIn to acquire information about the latest developments in the industry. You can join data communities or groups and participate in online or offline events and conferences to meet industry experts. Use this opportunity to turn your connections into referrals to gain an edge in your selection process.
2. Follow-Up Letter or Email: Whenever you apply for a job, ensure that you send in a follow-up letter or email if there is a delay in communication from the recruiter. You should send this email after a week of appearing for an interview. This reiterates your enthusiasm for the job position. In addition, you can ask specific questions about the process, company, or role. Refer to this blog on how to ask for an interview result for a better understanding.
3. Volunteer Your Services: Volunteering is one of the best ways to join an organization. While few organizations may offer remuneration for the same, most of the volunteer opportunities offer only a letter of recommendation for the candidates. Nonetheless, this is a good opportunity to build an impressive resume and gain industry experience. 
4. Reach Out to Employers Directly: Many organizations build a candidate database to fulfill their hiring needs from time to time. Instead of inviting fresh applications, they directly call candidates from their database for interviews. So, email the hiring manager with your resume and cover letter expressing why you want to work at their company.

Conclusion

This guide on how to get a job in data analytics leads you to a strategic blend of education, skill development, and practical experience. You need to obtain a relevant degree and become proficient in skills like statistical analysis, programming in Python, R, or SQL, data visualization, etc. Further, gaining experience through projects, internships, and certifications is crucial. The tips discussed above will help you navigate the path to a rewarding career in data analytics. 

If you are deliberating whether to work as a data analyst or data scientist, check out our blog on data science vs. data analytics to decide which field is for you.

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