Data Analyst: Career Path and Qualifications

Trained data analysts are some of the world’s most sought-after professionals. Because the demand is so high and the supply of people who can really do the job well is so limited, data analysts command huge salaries and great benefits, even at the entry level.

Data analyst positions can be found in a diverse mix of companies and industries. Any business that uses data needs data analysts to analyze it. Some of the most important jobs in data analysis involve using data to make investment decisions, target clients, assess risk, or decide on capital allocations.

Key points to remember

  • The role of the data analyst has become increasingly important in the internet age, with job opportunities in industries ranging from finance and marketing to social media.
  • In addition to becoming familiar with computers, data analysts should also be familiar with statistical methods and models.
  • Big data and machine learning are among the leading applications of data analysis.

What do data analysts do?

Data analysts take mountains of data and probe it to spot trends, forecast, and extract insights to help their employers make more informed business decisions. The career path you take as a data analyst depends a lot on your employer. Data analysts work on Wall Street at major investment banks, hedge funds, and private equity firms. They also work in the healthcare industry, marketing, and retail. Usually, data analysts are everywhere. You can also find them at major insurance companies, credit bureaus, tech companies, and almost any industry you can think of. Big tech companies like Meta (formerly Facebook) and Google are analyzing big data to a dizzying degree. To do this, they employ many of the best data analysts for a variety of purposes, including advertising and internal analytics, as well as a lot of user analytics.

In financial institutions such as investment banks, the management path is the most common career path that analysts take at the entry level. If you prove that you are among the best in your hiring group, your superiors will see you as someone who can guide the next group of hires. Prove yourself in management and you might consider a career as a department manager or vice president.

Many companies also refer to data analysts as information scientists. This classification usually involves working with a business owner’s database. Many IT professionals work with basic database infrastructures, thereby gaining skills in other applicable technical areas such as construction and development of data infrastructures. The government sector is one such sector that employs and relies heavily on information scientists for data collection, extraction and analysis. Insurance and healthcare companies also have in-depth data infrastructures that also require information scientists.

Technology companies are unique because, as technology changes rapidly, business dynamics often change as well. Departments are constantly being created to meet new challenges and seize new market opportunities. Technology data analysts who excel in their existing roles are typically the first to be chosen to be leaders when new departments are created. This provides an opportunity to lead others and allows you to take ownership of a segment of the business.

Overall, data analysts generally have a dynamic skill set. They are good at working with numbers and details. They are also confident and organized to handle multiple tasks, data programs, and data flows. Finally, most data analysts usually also have strong presentation skills, as they typically need to present their analysis visually and / or orally on a regular basis.

Overview of the data analytics industry

Jobs in the data analytics industry are plentiful, the salaries are high, and the career paths you can take are plentiful. Data analytics offers a wide variety of opportunities across industries and company levels. As such, it can be difficult to determine expectations for salary and growth. The Bureau of Labor Statistics offers several different classifications for wages and growth.

Financial Analyst

The category of financial analysts is generally the broadest classification for data analysts. This type of role can include business analysts, management analysts, and a wide variety of different types of investment analysts. BLS data from 2020 shows the average hourly salary for a financial analyst at $ 40.22 with an average annual salary of $ 83,660. Hourly wages can range from $ 23 to $ 76. Financial analysts in New York make the most of it with an average hourly wage of $ 63. The BLS expects this category of workers to grow at a faster than average rate of 6% through 2030.

Market research

A second Bureau of Labor classification that is often sought after for data analyst salary expectations is the market research analyst category. As of 2020, this category displays the average hourly wage at $ 31.64 with an annual wage expectation of $ 65,810. Hourly wages for market researchers can range from $ 17 to $ 44. The BLS also expects strong growth in this category with a growth rate of 22% through 2030.

Big Data and Machine Learning

As the business world evolves, so does the uses of data evolve with it, with the demand for big data technology, big data analytics, and machine learning showing some of the most important areas of growth. These types of big data technologies are increasingly being incorporated into the data analysis programs of large universities in the United States and around the world, of which there are many.

The majority of colleges in the United States offer data analysis or data science as a major or minor. Beyond the bachelor’s degree, there are also a large number of master’s programs in data science. If you want to develop your skills in a more flexible or shorter time frame, there are also several certification programs and courses available at a variety of educational institutions.

Data Analyst Qualifications

Graduating from a data analysis program, especially if you have a good cumulative grade point average and a high ranking in your class, should lead to an entry data analysis position without too much of problems. Even a less math, statistics, or economics-focused degree from a reputable university is enough to get your foot in the door. Although the work is entry level, the pay is higher than that of seasoned professionals in most fields.

As we’ve seen, some of the best data analytics jobs can run as high as $ 100,000 per year in the first year out of college. Experienced professionals can do double or more of what an entry-level data analyst does. The experience can come from working as a junior analyst or in a related field, such as investment analysis. However, education is often the most important thing on your resume when you apply for a data analyst job. Few are hired without strong academic performance in fields of study related to mathematics.

Data analyst career paths

Below is a list of some of the many different roles you may come across when researching or considering data analysis.

  • Business analyst: analyzes company-specific data.
  • Management reports: reports data analysis to management on business functions.
  • Business Strategy Analyst: This type of position will focus on analyzing company-wide data and advising management on strategic direction. This role can also be focused on mergers and acquisitions.
  • Compensation and Benefits Analyst: Usually part of a human resources department that analyzes data on employee compensation and benefits.
  • Budget Analyst: Focuses on the analysis and reporting of a specified budget.
  • Insurance Underwriting Analyst: Analyzes individual, company and industry data to make decisions on insurance plans.
  • Actuary: Analyzes mortality, accident, illness, disability and retirement rates to create probability tables, risk forecasts and liability planning for insurance companies.
  • Sales Analysis: Focuses on sales data that helps support, improve, or optimize the sales process.
  • Web Analytics: Analyzes a dashboard of analytics around a specific page, topic, or website comprehensively.
  • Fraud Analysis: Monitors and analyzes fraud data.
  • Credit Analysis: The credit market offers a broad need for analysis and information science in the areas of credit assessment, credit monitoring, loan risk, loan approvals and credit analysis. loan analysis.
  • Business Product Analyst: Focuses on analyzing the attributes and characteristics of a product as well as the responsibility of advising management on the optimal pricing of a product based on market factors.
  • Social Media Data Analyst: Social media and growing tech companies rely on data to create, monitor and advance the technology and offerings that social media platforms rely on.
  • Machine Learning Analyst: Machine learning is a developing technology that involves programming and powering machines to make cognitive decisions. Machine learning analysts can work on a variety of aspects including data preparation, data flows, results analysis, and more.

Sean N. Ayres