Statistical Analytics Careers Explained: Jobs, Duties, Salaries

Written by Coursera • Updated on

Statistical analytics is a high demand career with great benefits. Learn how you can apply your statistical and data science skills to this growing field.

[Featured image] Analysts study sheets of paper containing statistical harts and graphs

If you are a whiz at data and statistics, statistical analysis could be a great career match for you. The rise of big data, machine learning, and technology in our society has created a high demand for statistical analysts, and it's an exciting time to develop these skills and find a job you love. Read on to learn more about statistical analysis, its benefits, and how to take your next steps in this rewarding career.

What exactly is statistical analytics?

Statistical analysis is collecting and analyzing data to find useful information. Have you ever been told that smoking cigarettes causes cancer? What about how eating carrots can improve your eyesight? These insights come from the work of statistical analysts. Many research studies collect large volumes of information from participants, often without a clear end goal. Statistical analysts have the exciting opportunity to take this raw data and find correlations between different variables. They can use this info in a wide range of areas, such as finding new scientific discoveries, improving the health of our communities, and informing business decisions. When you go into statistical analytics, you can apply your knowledge of statistics and data to an area you are passionate about.

As a statistical analyst, you are also in charge of ensuring the data is not biased. While companies or organizations may want a particular product or system to be proven effective, you may ensure that the data supports the information given to the public without bias. This is especially important to ensure people can make informed decisions throughout their daily lives. Many people choose careers in statistical analytics because they can directly contribute to the health of our community. 

Types of statistical analysis

While many fields use statistical analysis, you can focus on one of two main types: descriptive or inferential. Deciding which area better suits your interest and skill set can ensure you are in the right career.

Descriptive statistical analysis

Descriptive statistical analysis occurs when you summarize the findings of a set of data without creating conclusions about the contents. For example, if a business gave you a book of its expenses, you might summarize what percentage of the money it spent on different categories of items. For this position, you will primarily present graphs, tables, and charts to give large amounts of information in concise, easily understandable formats. Typically, the company or person uses this data to inform decisions and make the next steps. 

Inferential statistical analysis

Inferential statistics takes the results of descriptive statistics one step further. Inferential statistical analysis allows you to draw conclusions about the data and make recommendations. For example, instead of only summarizing the business's expenses, you might go on to recommend in which areas to reduce spending and suggest an alternative budget. Businesses use inferential statistical analysis often to inform company decisions and in scientific research to find new relationships between variables. 

What does statistical analytics involve?

When you work as a statistical analyst, your main job will likely focus around making large sets of data understandable for a more general audience. You use your math and data skills to translate big numbers into easily digestible graphs, charts, and summaries. Typical job responsibilities of statistical analysts include:

  • Extracting and organizing large sets of raw data

  • Determining which data is relevant and which to disqualify

  • Developing new data collection strategies

  • Meeting with clients and professionals to review data analysis plans

  • Creating data reports and easily understandable representations of the data

  • Presenting data

  • Interpreting the results of the data

  • Creating recommendations for company or personal decisions

Your job responsibilities will differ depending on whether you work for a federal agency, a private company, or another business sector. Many industries need statistical analysts, so exploring your passions and seeing how you can best apply your data skills can be exciting. 

Typical skills needed for statistical analytics: 

Because most of your job responsibilities will likely focus on data and statistical analysis, mathematical skills are crucial. High-level math skills can help you fact-check your work and create strategies to analyze the data, even if you use software for many computations. When honing in on your mathematical skills, focusing on statistics—specifically statistics with large data sets—can help set you apart when searching for job opportunities. Competency with computer software and learning new platforms will also help you excel in more advanced positions and put you in high demand.

Data analytics, problem-solving, and critical thinking are vital skills to help you determine the data set’s true meaning and bigger picture. Often, large data sets may not represent what they appear to on the surface. Being able to think critically about factors that may influence the data set, how to create an analysis plan best, and finding trends without bias will require you to think clearly and creatively. 

To go above and beyond in your data analytics career, honing in on database management skills, keeping up to date with statistical methodology, and improving research skills can help you excel in the workplace. These skills are in high demand by employers and expand the responsibilities you can take on while on the job. These skills take time to build, so starting with introductory courses and having patience while you build skills is important.

Common software used in statistical analytics jobs

Statistical analysis often involves computations with a volume of data much too large to compute by hand. The good news is that many kinds of statistical software have been developed to help analyze data effectively and efficiently. Gaining mastery over this statistical software can make you look attractive to employers and allow you to work on more complex projects. 

Statistical software is beneficial for both descriptive and inferential statistics. You can use it to generate charts and graphs or perform computations to draw conclusions and inferences from the data. While the type of statistical software you will use will depend on your employer, common software used are:

  • SAS

  • R

  • SPSS

  • Minitab

  • Stata

Pathways to a career in statistical analytics

Many paths to becoming a statistical analyst exist, but most jobs in this field require a bachelor’s degree. Employers will typically look for a degree in an area that focuses on math, computer science, statistics, or data science to ensure you have the skills needed for the job. If your bachelor’s degree is in another field, gaining experience through entry-level data entry jobs can help get your foot in the door. Many employers look for work experience in related careers such as being a research assistant, data manager, or intern in the field.

Earning a graduate degree in statistical analytics or a related field can also help you stand out on your resume and demonstrate a deep knowledge of the skills needed to perform the job successfully. Generally, employers focus more on making sure you have the mathematical and data analytical skills required to perform complex statistical analytics on its data. After all, you will be helping them to make decisions, so they want to feel confident in your ability to advise them in the right direction.

Read more: Your Guide to a Career as a Statistician—What to Expect

How much do statistical analytics professionals earn? 

Statistical analysts earn well above the national average and enjoy many benefits on the job. There are many careers utilizing statistical analytics, so comparing salaries can help determine if the job benefits align with your expectations.

Actuary

Median annual salary: $105,900

Job outlook for 2020 to 2030: 24% [1]

Data scientist

Median annual salary: $108,660

Job outlook for 2020 to 2030: 22% [2]

Financial risk analyst

Median annual salary: $81,410

Job outlook for 2020 to 2030: 6% [3]

Investment analyst

Median annual salary: $81,410

Job outlook for 2020 to 2030: 6% [4]

Operational research analyst

Median annual salary: $82,360

Job outlook for 2020 to 2030: 25% [5]

Market researcher

Median annual salary: $63,920

Job outlook for 2020 to 2030: 22% [6]

Statistician

Median annual salary: $92,280

Job outlook for 2020 to 2030: 33% [7]

Read more: How Much Do Statisticians Make? Your 2022 Statistician Salary Guide

Statistical analyst job outlook

Statistical analyst jobs have a much higher projected growth than the national average, with some as high as 33 percent projected growth [9]. As we create more ways to collect data worldwide, there will be an increased need for people able to analyze and make sense of the data. This is good news for those starting and interested in pursuing this career—the jobs aren’t going anywhere. Take your time, build your skills, and you’ll be analyzing data before you know it.

Ready to take the next step in your career?

Statistical analytics is an expanding field with great career benefits and outlook. It could be an excellent career match for those with an affinity for math, data, and problem-solving. If you want to begin your career as a statistical analyst but don’t have experience in this subject area, taking a course on Coursera, such as Foundations: Data, Data, Everywhere offered by Google, can help you get your foot in the door and determine whether this is the right career path for you.

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Article sources

1

US Bureau of Labor Statistics. "Actuaries, https://www.bls.gov/ooh/math/actuaries.htm." Accessed November 9, 2022.

Written by Coursera • Updated on

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