Predictive Analytics Career Path: Unlocking Data-driven Decision-Making

To build a career in predictive analytics, consider developing your expertise with entry-level jobs like a junior analyst or business intelligence analyst to gain experience in the field before moving into mid-level positions like data scientist or marketing data analyst. After you’ve gained several years of experience and potentially earned more credentials or an advanced degree, you might qualify for senior or management roles. 

Predictive analytics is an important component of data analytics, a growing field helping companies and organizations analyze and interpret data. It is one of four types of data analysis that help companies understand what happened in the past, why, what might happen in the future, and what actions could be taken to change or take better advantage of that future scenario. 

• Descriptive: What happened? 

• Diagnostic: Why?

• Predictive: What will happen next?

• Prescriptive: What should you do?

Learn more about what your predictive analytics career path might look like, from an entry-level role to leadership positions. 

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What is predictive analytics? 

Predictive analytics is a type of data analytics that uses data about what’s already happened to predict or better understand what could happen in the future. Predictive analytics uses statistical modeling, data mining, and machine learning to reduce risk, improve efficiency, and make data-driven decisions. 

In data analytics roles using predictive analytics, you might use types of predictive modeling such as: 

• Classification models: Supervised machine learning models that categorize data

• Clustering models: Unsupervised machine learning models that sort data into clusters based on shared characteristics

• Time series models: Models that track how data changes over time from a signal, such as a stock price or seasonal sales

Predictive analytics examples

You can use predictive analytics to gain insight into what could happen in the future. A few examples of how organizations in different industries use predictive analytics include: 

• Marketing: You can use predictive analytics to understand what customers want, how customers behave, and how to avoid churn by increasing customer success.

• Logistics: Predictive analytics can help you optimize your supply chain by enabling you to adjust inventory and product pricing according to demand. 

• Finance: Banks and other lending institutions can use predictive analytics to estimate which applicants would be good loan or credit candidates. Predictive analytics can also forecast the performance of financial products, giving you insight into which investments might be lucrative. 

Entry-level predictive analytics jobs

For many jobs in predictive analytics, you’ll need to earn a bachelor’s degree. Sometimes, you can find a junior or entry-level position to gain experience while you finish your formal education. In this case, you may need a certification or relevant credential to demonstrate you have some knowledge of data analysis principles. Two entry-level role examples include junior data analyst and business intelligence analyst. 

Junior data analyst

Average salary in the US (Glassdoor): $74,013 [1]

Job outlook (projected growth from 2032 to 2033): 36 percent [2]

As a junior data analyst, you will support a team of analysts, helping a company or organization make sense of their data. In this role, you will create reports, validate data, and provide support to senior data analysts as needed. You can work as a junior analyst in various industries like financial services, retail, meteorology, energy, and more. 

Business intelligence analyst

Average salary in the US (Glassdoor): $101,417 [3]

Job outlook (projected growth from 2032 to 2033): 11 percent [4]

As a business intelligence analyst, you will use your skills in predictive analytics to help companies make data-driven decisions with their data. You will collect and analyze data to suggest ways your company can improve its processes, identify new markets or business opportunities, and communicate technical concepts to stakeholders and other non-technical team members. 

Mid-level roles in predictive analytics 

As you start to gain experience in the field, you may qualify for positions with more significant responsibilities. For mid-level careers in predictive analytics, you will need a bachelor’s degree. You may also see more positions that prefer you to have a master’s degree. You could study areas like mathematics, statistics, computer science, or business.Two potential mid-level careers to consider include marketing data analyst and data scientist.

Marketing data analyst

Average salary in the US (Glassdoor): $71,180 [5]

Job outlook (projected growth from 2032 to 2033): 8 percent [6]

As a market data analyst or market research analyst, you will analyze data to help companies understand how customers feel, what customers want, and how to reach these customers with marketing strategy. In this role, you will gather and analyze data before submitting a report, recommendation, or other summary of your findings to company leadership. 

Data scientist

Average salary in the US (Glassdoor): $118,075 [7]

Job outlook (projected growth from 2032 to 2033): 36 percent [2]

As a data scientist, you can unlock the meaning behind data in many different industries, including computer systems, insurance, management, consulting, or scientific research in development. You could work on any number of projects, depending on your industry. In this role, you will determine what data you need to find the solution you’re looking for, then gather and analyze that data to present your findings to stakeholders. 

Senior roles in predictive analytics

After you’ve gained several years of experience working in data analytics, you may qualify to step into a senior or leadership role. Depending on your experience and industry, you may need some advanced education to qualify for roles at a senior level. You can also pursue certification or certificates to continue improving your skill set and resume. At this level, you may still work directly on data analytics projects and spend more time managing other analysts and directing data strategy. Two senior and leadership roles in predictive analytics include senior data analyst and data analytics manager. 

Senior data analyst

Average salary in the US (Glassdoor): $120,190 [8]

Job outlook (projected growth from 2032 to 2033): 36 percent [2]

As a senior data analyst, you will be a leader within your team working on data analysis projects for companies and organizations. You might also be able to mentor junior data analysts. In this role, your focus will include sharing data-driven insights, managing the company’s data governance, and implementing data strategies. You will help guide your team's work, and you may directly manage teams or projects. 

Data analytics managers

Average salary in the US (Glassdoor): $146,179 [9]

Job outlook (projected growth from 2032 to 2033): 17 percent [10]

As a data analytics manager, you will lead a team of data analysts. You’ll typically find data analytics jobs at larger companies and firms with a larger analytics staff. In this role, you’ll help develop data strategies, monitor your department's performance, and report to senior leadership. In this management position, you’ll direct and support your team by overseeing workflow and helping resolve challenges as they arise. 

Predictive analytics skills

No matter what role you take within predictive analytics, a few key skills will be important in every job role, from entry-level to leadership. These include: 

• Mathematics and statistics: Math skills, specifically skills in statistics, linear algebra, and calculus, will be important if you work with data. 

• Data visualization: The ability to translate data into visualizations that make it easier for non-technical people to understand data will be helpful as you present your findings to others within your organization and help you look at data in new ways. 

• Programming languages: You will need to understand some programming languages while you work with machine learning algorithms to manipulate data. A few languages that can be important for data professionals are R, Python, SQL, and NoSQL. 

• Communication: Communication is important because you may need to translate highly technical concepts to members of your team or organization who aren’t comfortable with technical language. 

• Analytical thinking: One thing all analyst jobs have in common is that you will need to analyze data for useful insights. You’ll need critical and analytical thinking to succeed.

Begin your predictive analytics career path on Coursera.

Your predictive analytics career path might look different depending on what industry you want to work in. You will generally start in junior-level roles and work your way up, which may require additional training. If you want to explore certifications that can help you take your career to the next level, or if you want to explore job-ready skills that can help you find an entry-level job, you can find programs on Coursera. For example, you could enroll in the IBM Data Analyst Professional Certificate for IBM training as a data analyst, or you could enhance your skill set with IBM Data Analytics with Excel and R Professional Certificate.

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IBM Data Analyst

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IBM Data Analytics with Excel and R

Prepare for a career in data analytics. Gain the in-demand skills and hands-on experience to get job-ready in less than 3 months. No prior experience required.

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Beginner level

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Average time: 3 month(s)

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Skills you'll build:

Data Visualization (DataViz), Data Science, Spreadsheet, Data Analysis, Microsoft Excel, IBM Cognos Analytics, Relational Databases (RDBMS), Dashboard, Data Visualization, R Programming, Pivot Table, Statistical Analysis, Data Structure, cognos analytics, Pivot Charts, Linear Regression, Exploratory Data Analysis, Select (Sql)