analytics career path

Top 10 Analytics Career Path 2023: Salaries and Qualifications


When pursuing a profession in data analytics, it is critical to consider the big picture. What happens after you become a certified data analyst? What is the normal professional path you can anticipate? Is one available?

In this piece, we’ll look at some of the most typical career pathways for data analysts. By the conclusion, you’ll know how to get started as a data analyst and where your career may take you once you’ve gotten your foot in the door.

So, what is the average job path for a data analyst? Let us investigate.

What Is a Data Analyst?

A data analyst is a wide phrase for someone who is hired to study data and generate insights from which viewers might act. Data analysts are among the most in-demand specialists in the world.

Due to strong demand and a shortage of skilled workers, data analysts typically receive higher-than-average pay and benefits, particularly at the entry-level.

Jobs for data analysts are available in a variety of businesses and sectors. Analyzing data to target customers, evaluate risks, allocate resources, or make financial decisions is a component of some of the greatest jobs in data analysis.

What Do Data Analysts Do?

Data analysts sift through masses of data to identify trends, forecast future trends, and extract information to assist their employers in making more informed business decisions. The path you pursue as a data analyst is heavily influenced by your employment.

What are their working hours?

Data analysts on Wall Street are employed by big investment banks, hedge funds, and private equity firms.

They also work in the healthcare, marketing, and retail industries. Data analysts can be found almost anywhere.

They can also be found in practically every business, including huge insurance corporations, credit bureaus, technological companies, banks, and manufacturing. Companies like Meta and Google analyze massive amounts of data. To accomplish this, they hire several of the top data analysts for a variety of objectives, including advertising, internal analysis, and extensive user study.

The managerial track is the most typical career route for analysts starting in financial organizations such as investment banks.



Data Analyst Qualifications

1. Education

Graduating from a data analysis program, especially if you have a high-grade point average and a high ranking in your class, should easily lead to an entry-level data analysis career.

Even a general degree in mathematics, statistics, or economics from a good university will get you in the door.

Most institutions in the United States offer both a major and a minor in data analytics or data science.

There are numerous data science master’s degrees available in addition to the bachelor’s degree.

If you want to develop your abilities in a more flexible or shorter timeframe, numerous educational institutions offer a variety of certification programs and courses.

2. Skills

Overall, data analysts have diverse skill sets. They excel at dealing with numbers and details. They are also self-assured and well-organized when managing many activities, data programs, and data flows.

Data analysts are normally required to have great presentation abilities because they are frequently requested to convey their analysis orally or visually.

3. Experience

Working as an entry-level analyst or in a related industry, such as investment analysis, might provide experience.

When applying for a data analyst job, your degree is frequently the most important element on your resume.

Only persons are hired if they have strong academic records in math-related study subjects.

Data Analyst Career Paths

The following is a list of the various positions you may face when looking for or contemplating data analysis.

  • Analyzes business-specific data as a business analyst.
  • Management reporting: provides management with data analytics on company functions.
  • Corporate strategy analyst: analyzes company-wide data and provides strategic advice to management. This position may also be concerned with mergers and acquisitions.
  • Compensation and benefits analyst: A person who analyzes employee compensation and benefits data as part of a human resources department.
  • Budget analyst: A budget analyst focuses on the study and reporting of a certain budget.
  • Insurance underwriting analyst: analyzes individual, company, and industry data to make insurance plan recommendations.
  • Actuary: analyzes mortality, accident, sickness, disability, and retirement rates to provide probability tables, risk forecasts, and liability plans for insurance companies.
  • Sales data that supports, enhances, or optimizes the sales process is the focus of sales analytics.
  • Web analytics: comprehensively analyzes a dashboard of analytics centered on a certain page, topic focus, or website.
  • Fraud analytics: the monitoring and analysis of fraud data
  • Credit analytics: There is a high demand for analytics and information science in credit reporting, credit monitoring, lending risk, lending approvals, and lending analysis in the credit market.
  • Business product analyst: analyzes a product’s traits and characteristics and advises management on the best pricing of a product based on market considerations.
  • Social media data analyst: Data is used by social media platforms and rising digital companies to construct, monitor, and advance the technologies and offers that they rely on.
  • Machine learning analyst: may work on a variety of tasks such as data preparation, data feeds, result analysis, and more.

Data Analytics Career Outlook

Jobs in the data analytics business are plentiful, pay is good, and career routes are numerous. Data analytics provides numerous opportunities across industries and organizational levels.

Right out of college, some of the finest jobs in data analysis may pay nearly $100,000. Experienced workers can earn significantly more.

The Bureau of Labor Statistics lists a few different categories of analysts, as well as their current income and job outlook.

1. Financial Analyst

  • Average hourly wage: $45.95, with a range of $28.34 to $81.70.
  • The average annual wage is $95,570.
  • The highest-paid location is New York, where the average hourly income is $67.73.2
  • Growth: The BLS anticipates that this group of workers will grow at a faster-than-average rate of 9% through 2031.

 2. Market Research Analyst

  • Hourly wages range from $18.40 to $63.393 on average.
  • The average annual pay is $78,880.
  • New York is the highest-paying location.
  • Growth: The BLS anticipates that this category of workers will grow at a faster-than-average rate of 19% through 2031.

 3. Management Analyst

  • $50.325 is the average hourly wage.
  • The average annual salary is $104,660.
  • New York is the highest-paying location.
  • Growth: The BLS anticipates that this group of workers will grow at a faster-than-average rate of 11% through 2031.


Is data analysis simple or difficult?

This is determined by a variety of criteria, including your aptitudes, interests, education, and experience. Some people are born with the aptitude to evaluate data, while others struggle.

What Skills Do I Need to Be a Data Analyst?

In general, you’ll need to be strong in math and science, as well as have a degree that matches the field in which you wish to specialize.

Is it Possible to Work as a Data Analyst Without a Degree?


It is feasible to work as a data analyst without a degree if you can persuade an employer that you can do the job. In a competitive environment, such as the job market, education, additional credentials, or experience can provide you with an advantage over other applicants.


Data analysts work in a wide range of businesses, and this trend is likely to continue. Data generated by programs and technology is increasingly being used by businesses to make decisions. Data is collected, sorted, and presented using artificial intelligence and machine learning.

However, technology has not yet progressed to the point where human intervention is no longer required; all it can do is change data as designed. Humans are still required to analyze results and add views to data that algorithms cannot, therefore demand for data analysts is expected to stay stable.

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