Data Analyst: Career Path and Qualifications

Skilled data analysts are some of the most sought-after professionals in the world. Because the demand is so strong, and the supply of people who can truly do this job well is so limited, data analysts command huge salaries and excellent perks, even at the entry-level.

Data analyst jobs can be found throughout a diverse mix of companies and industries. Any company that uses data needs data analysts to analyze it. Some of the top jobs in data analysis involve using data to make investment decisions, target customers, assess risks, or decide on capital allocations.

What Do Data Analysts Do?

Data analysts take mountains of data and probe it to spot trends, make forecasts, and extract information to help their employers make better-informed business decisions. The career path you take as a data analyst depends in large part on your employer. Data analysts work on Wall Street at big investment banks, hedge funds, and private equity firms. They also work in the healthcare industry, marketing, and retail. In general, data analysts are everywhere. You can also find them at large insurance companies, credit bureaus, technology firms, and in almost any industry you can think of. Big tech companies such as Meta (formerly Facebook) and Google analyze big data to a dizzying degree. To do so, they employ many of the top data analysts for a variety of purposes including advertising and internal analysis along with a great deal of user analysis.

At financial institutions such as investment banks, the management track is the most common career path analysts take from the entry-level. If you prove that you are among the best of your hire group, your superiors are going to look to you as someone who can shepherd the next group of hires that come in. Prove yourself in management, and you could be looking at a career as a department head or vice president.

Many companies also label data analysts as information scientists. This classification typically involves working with a company’s proprietary database. Many information scientists work with core database infrastructures thus also gaining skills in other applicable technical areas such as data infrastructure building and development. The government sector is one such sector that employs and relies heavily on information scientists for data collection, mining, and analysis. Insurance and health care companies also have deep data infrastructures that require information scientists as well.

Technology companies are unique because as technology changes rapidly, the dynamic of the company often changes too. Departments are constantly being created to tackle new challenges and pursue new market opportunities. Technology data analysts who excel in their existing roles are usually the first ones to be chosen to be leaders when new departments are created. This provides an opportunity to lead others, and it allows you to take ownership in a segment of the company.

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

Overview of the Data Analytics Sector

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

Financial Analyst

The financial analyst category is generally the most widely encompassing 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 wage for a financial analyst at $40.22 with an average annual salary of $83,660. Hourly salaries can range from $23 to $76. Financial analysts in New York make the most at an average hourly wage of $63. The BLS expects this class of workers to grow at a faster than average rate of 6% through 2030.

Market Research

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

Big Data and Machine Learning

As the business world evolves the uses of data are also evolving with it, with demand for big data technology, big data analysis, and machine learning showing some of the top growth areas. These types of big data tech are being more heavily integrated into data analysis programs at major universities in the United States and across the world of which there are plenty.

The majority of colleges in the United States offer data analytics or data science as both a major or minor. Beyond the bachelor’s degree, there are also a vast number of data science master’s programs. If you are interested in building your skills in a more flexible or shorter timeframe there are also multiple certification programs and courses available from a variety of educational institutions.

Data Analyst Qualifications

Graduating from a data analysis program, particularly if you have a strong grade point average and a high ranking in your class, should lead to an entry-level data analysis position without much trouble. Even a less-focused degree in mathematics, statistics, or economics from a reputable university is enough to get your foot in the door. Though the job is entry-level, the pay is more than seasoned professionals in most fields make.

As discussed, some of the top jobs in data analysis can reach as high as $100,000 annually during the first year out of college. Experienced professionals can make double or more what an entry-level data analyst makes. Experience can come from working as an entry-level analyst or from a related field, such as investment analysis. However, education is often the most important thing on your resume when applying for a data analyst job. Few people get hired without strong academic performances in math-related fields of study.

Data Analyst Career Paths

Below is a list of some of the many different roles that you may encounter when searching for or considering data analysis.

• Business analyst: analyzes business-specific data.
• Management reporting: reports data analytics to management on business functions.
• Corporate strategy analyst: this type of role will focus on analyzing company-wide data and advising management on strategic direction. This role may also be focused on mergers and acquisitions.
• Compensation and benefits analyst: usually part of a human resources department that analyzes employee compensation and benefits data.
• Budget analyst: focuses on the analysis and reporting of a specified budget.
• Insurance underwriting analyst: analyzes individual, company, and industry data for decisions on insurance plans.
• Actuary: analyzes mortality, accident, sickness, disability, and retirement rates to create probability tables, risk forecasting, and liability planning for insurance companies.
• Sales analytics: focuses on sales data that helps to support, improve, or optimize the sales process.
• Web analytics: analyzes a dashboard of analytics around a specific page, topic focus, or website comprehensively.
• Fraud analytics: monitors and analyzes fraud data.
• Credit analytics: the credit market offers a wide need for analytics and information science in the areas of credit reporting, credit monitoring, lending risk, lending approvals, and lending analysis.
• Business product analyst: focuses on analyzing the attributes and characteristics of a product as well as responsibility for 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 build, 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 feeding machines to make cognitive decisions. Machine learning analysts may work on a variety of aspects including data preparation, data feeds, analysis of results, and more.