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Career Development

What Jobs Can You Get After a Data Analytics Bootcamp?

General Assembly
February 6, 2023

In 2022, the estimated data generated equaled 97 zettabytes (that’s nearly 100 billion terabytes). As companies generate more data, they need data analysts to interpret it. With an acute skills shortage, entry-level data analyst jobs are a great place to start or restart a career.

According to research from the World Economic Forum, data analysts and scientists are the most in-demand job worldwide. Data analysts help companies solve business problems by collecting, cleaning, and interpreting data with statistical methods and analysis software.

Since the field is evolving and growing so fast, four-year degree programs can’t produce graduates fast enough or keep up with the changing skills needed for the workplace. One option to bypass the four-year degree or switch careers into data analytics is to complete a data analytics bootcamp.  

What is a Data Analytics Bootcamp?

A data analytics bootcamp is a short-term educational program that teaches participants the top skills they need to qualify for an entry-level data analytics job. Data analytics bootcamps use a mix of instructor-taught curriculum and independent work to help students get up to speed on top skills like data analysis, Python, PowerBI, and data visualization.

How Does a Data Analytics Bootcamp Work?

The format for a data analytics bootcamp can vary. Some take place in a classroom while others are online or hybrid. If you choose an online course, you can expect it to be interactive and collaborative. Beyond class time, you’ll work on independent projects, receive feedback, and have access to office hours with instructors.

There are two models of bootcamps. One is part-time, which can be completed simultaneously with a job or caregiving responsibilities. A part-time bootcamp allows for flexibility if doing a full-time bootcamp is not feasible.

The other type, an immersive bootcamp, is where the participant devotes the majority of their time to learning, just like a full-time class load or job. Participants can complete an immersive data analytics bootcamp in just 12 weeks, allowing them to enter the job market sooner. Another benefit of the immersive model is that students can retain learning better by being surrounded by the curriculum and applying technical skills to projects day in and day out.

Whichever model you choose, bootcamps use these methods to set students up for success.

Technical Skills

Many bootcamps work directly with employers to identify the top skills and software programs students need to be successful. At General Assembly, for example, students complete technical units in SQL, Excel, Tableau, PowerBI, and Python. In addition to technical skills, students learn statistical principles and how to use data responsibly.   

Collaboration

No matter the format, bootcamps require students to engage in digital collaboration and communication—just like they would in the workplace. Students benefit from feedback from expert instructors by going through the course with a cohort. Unlike a self-paced online course, bootcamps give students accountability from a structured timeframe and support from peers and instructors.

Career Preparation

Since bootcamps are designed for fast career entry, bootcamp programs offer career support for participants including resume review and interview preparation. Look for a bootcamp where you’ll create a capstone project and portfolio—a key asset for your job hunt.

You can also expect to interact with industry experts to make connections and get ready for job searching. Many bootcamps offer sessions like guest panels and hiring discussions throughout a bootcamp.

How To Choose the Right Bootcamp For You

With so many bootcamps out there, it can be difficult to choose the right best data analytics certification. Ask yourself these questions to help yourself weigh what the right step is for you:

  1. Will part-time or immersive work best with your current lifestyle and financial situation?
  2. Will in-person, online, or hybrid fit your learning style best?
  3. What do alumni say about the program? Read reviews or reach out to graduates to get real-world stories and feedback about specific programs.
  4. Is there a specific industry or specialty area that you want to pursue within data analytics? If so, read job descriptions and make sure that the bootcamp you choose teaches the skills and programs needed.

It’s always good to research job titles and possible employers even before starting a program. Data analytics jobs are not one-size-fits-all. To learn what kind of job options are available for data analytics bootcamp graduates, check out four possible career paths below.

Top 4 Careers To Pursue After a Data Analytics Bootcamp

Every kind of business needs data analytics to gather, clean, and interpret data and provide visualizations for decision-makers. The most common job title you’ll see is—no surprise here—data analyst.

Data analyst is the generalist title that many companies use for analyst roles, though the exact responsibilities vary. Some companies use the junior data analyst or senior data analyst, signaling the role’s seniority. You may also see jobs like “Data Analyst I” or “Operational Analyst IV,” indicating different pay grades with Roman numerals.

Beyond a generalist role, here are four data analyst specialties you should know about.

Business Analyst

Business analysts perform analyses to glean business intelligence – insights that help companies make decisions on revenue, marketing, or operations. You can find examples of this in both business-to-business (B2B) and business-to-consumer (B2C) organizations.

Let’s look at consumer products and services as an example. As more and more companies enroll customers in accounts and loyalty programs, they generate valuable data about customer purchases along with website and app activity. These companies need analysts to give insights into buying patterns so they can set competitive pricing and improve their performance and revenue.

Walmart, for example, claims to have the “world’s largest private database”. Walmart embeds data analytics positions within its merchandising, human resources, and technology teams to solve business challenges and improve outcomes.

Companies also house huge amounts of data within customer relationship management software (CRM) systems. Employers hire business analysts to support CRM administrators and marketing teams by creating dashboards and reports and validating data with SQL queries.  

In a B2B setting, a consulting company like PricewaterhouseCoopers (PwC) may hire a business analyst to conduct competitive intelligence, analyze a client’s customer data, or develop and test financial models. Business analysts need to have strong project management skills as they may conduct projects for multiple departments or external clients.

Financial Analyst

From interest rates to portfolio performance to underwriting, financial services is an industry built on data. It should be no surprise that banks, hedge funds, and insurance companies are one of the world’s biggest employers of data analysts and data scientists.

There are many reasons financial services companies invest in data analysis to improve their business. On one hand, they need to mitigate risk. By analyzing the past performance of loans and portfolios, they can make better decisions about future pricing and which investments they should keep or sell.

Fraud is also a huge issue, responsible for $4.7 billion in losses a year for companies. Access to real-time customer data can help financial services companies detect and prevent fraud.

Financial analysts need to have a strong mathematical and statistical background to land a job in addition to relevant programming languages.

Healthcare Data Analyst

Experts valued the healthcare analytics market at $8.4 billion in 2021 and expect it to grow 31% by 2027. The world of healthcare and medical data is exciting because it offers the chance to join in on solving huge global issues like epidemiology, improving patient experiences and outcomes, and finding life-altering medical breakthroughs.

Healthcare providers need data analysts to manage and interpret data in clinical trials and safeguard patient data according to HIPAA compliance. They will also need data analysts and scientists to contribute to emerging fields like AI in healthcare.

To get hired in a healthcare data analyst job, you need experience with databases such as SQL and Access and data visualization programs like Tableau. A general background in healthcare and an understanding of healthcare compliance is helpful, but not required.

Data Scientist

One excellent career path that data analysts can pursue is becoming a data scientist. Data analysts and data scientists are often lumped together, but they are in fact separate job functions.

Data scientists perform more complex, advanced data analysis than data analysts. While a data analyst interprets structured, historical data, a data scientist may analyze raw data from multiple sources to forecast future performance or behavior. Data analysts typically solve a known and specified problem, while data scientists may comb through big data for insights without knowing what they’re solving for. Data scientists are also integral in developing the latest AI and machine learning technology.

Because of their advanced skill set, data scientists earn more on average and have high job security based on job projections. You may not be able to land a data science job straight out of a data analytics bootcamp, but you can take the leap into data science with a few years of data analyst experience under your belt or with a data science bootcamp.

Job Hunting Success Tips After a Data Analytics Bootcamp

Once you’ve completed a data analytics bootcamp, you can start searching for data analyst entry-level jobs. Whether you’re interested in a large company, a startup, or a remote data analyst job, you’ll have many options. Bootcamp alumni have a lot of assets at their fingertips, from workforce-ready technical skills to networks of employers and alumni.

1. Display Your Certification on Your LinkedIn Profile and Resume

First, show off your credentials. Add your certification and badge if you have one to your LinkedIn profile and post about some of the things you learned in the bootcamp. Make sure to add your bootcamp and updated skills to your resume to make it shine.

2. Showcase Your Work in a Portfolio

The best data analytics bootcamps help students create a portfolio as part of the coursework. If you created one during the bootcamp, you won’t have much work to do other than adding the portfolio to your LinkedIn profile or a personal website if you have one.

If you haven’t created a portfolio yet, think about how to take one or two of your best projects and build a narrative around them. Show the problem you chose, how you overcame challenges, and what the results and business impact were. Make sure to include data visualizations to make it pop. Need ideas? You can browse GA student portfolios for inspiration. 

3. Use Career Services

Most bootcamps offer career services for free, so there’s no excuse not to take advantage of it. Work with career services to review your resume, help you prep for a technical interview, or negotiate a salary. Many bootcamps partner directly with employers (GA has 19,000 hiring partners around the globe) and can connect you with recruiters.

4. Tap Into Your Network

Even if you’re coming in as an outsider to data analytics, chances are that you’re better connected than you think. Reach out to anyone connected to data analytics or companies you’re interested in working for. Set up informational interviews and find out as much as you can about the industry and potential job openings.

Keep up with the cohort members from your bootcamp. You’re advocates, not competitors, for job openings and can support each other through the job search process.

How To Become a Data Analyst With No Experience

With up-to-date technical skills and a little grit, it’s completely possible to become a data analyst with no experience. Data analysts need to be good with numbers and have an attention to detail. Next, they need hands-on experience analyzing data in programs such as Python, Tableau, and SQL.

A data analytics bootcamp can equip anyone with the technical and soft skills they need to enter the data analytics job market. Whether you become a financial analyst, a healthcare analyst, or a business analyst, you can look forward to a fast-paced career on the cutting edge of technology and business evolution.

A good analyst is invaluable to companies, providing insights and observations that affect decision-making at the highest levels. Ready to step into the gap?If you’re ready to explore all the job change options available after a data analytics bootcamp, fill out this short form to chat with our Admissions team. 

In 2022, the estimated data generated equaled 97 zettabytes (that’s nearly 100 billion terabytes). As companies generate more data, they need data analysts to interpret it. With an acute skills shortage, entry-level data analyst jobs are a great place to start or restart a career.

According to research from the World Economic Forum, data analysts and scientists are the most in-demand job worldwide. Data analysts help companies solve business problems by collecting, cleaning, and interpreting data with statistical methods and analysis software.

Since the field is evolving and growing so fast, four-year degree programs can’t produce graduates fast enough or keep up with the changing skills needed for the workplace. One option to bypass the four-year degree or switch careers into data analytics is to complete a data analytics bootcamp.  

What is a Data Analytics Bootcamp?

A data analytics bootcamp is a short-term educational program that teaches participants the top skills they need to qualify for an entry-level data analytics job. Data analytics bootcamps use a mix of instructor-taught curriculum and independent work to help students get up to speed on top skills like data analysis, Python, PowerBI, and data visualization.

How Does a Data Analytics Bootcamp Work?

The format for a data analytics bootcamp can vary. Some take place in a classroom while others are online or hybrid. If you choose an online course, you can expect it to be interactive and collaborative. Beyond class time, you’ll work on independent projects, receive feedback, and have access to office hours with instructors.

There are two models of bootcamps. One is part-time, which can be completed simultaneously with a job or caregiving responsibilities. A part-time bootcamp allows for flexibility if doing a full-time bootcamp is not feasible.

The other type, an immersive bootcamp, is where the participant devotes the majority of their time to learning, just like a full-time class load or job. Participants can complete an immersive data analytics bootcamp in just 12 weeks, allowing them to enter the job market sooner. Another benefit of the immersive model is that students can retain learning better by being surrounded by the curriculum and applying technical skills to projects day in and day out.

Whichever model you choose, bootcamps use these methods to set students up for success.

Technical Skills

Many bootcamps work directly with employers to identify the top skills and software programs students need to be successful. At General Assembly, for example, students complete technical units in SQL, Excel, Tableau, PowerBI, and Python. In addition to technical skills, students learn statistical principles and how to use data responsibly.   

Collaboration

No matter the format, bootcamps require students to engage in digital collaboration and communication—just like they would in the workplace. Students benefit from feedback from expert instructors and going through the course with a cohort. Unlike a self-paced online course, bootcamps give students accountability from a structured timeframe and support from peers and instructors.

Career Preparation

Since bootcamps are designed for fast career entry, bootcamp programs offer career support for participants including resume review and interview preparation. Look for a bootcamp where you’ll create a capstone project and portfolio—a key asset for your job hunt.

You can also expect to interact with industry experts to make connections and get ready for job searching. Many bootcamps offer sessions like guest panels and hiring discussions throughout a bootcamp.

How To Choose the Right Bootcamp For You

With so many bootcamps out there, it can be difficult to choose the right best data analytics certification. Ask yourself these questions to help yourself weigh what the right step is for you:

  1. Will part-time or immersive work best with your current lifestyle and financial situation?
  2. Will in-person, online, or hybrid would fit your learning style best?
  3. What do alumni say about the program? Read reviews or reach out to graduates to get real-world stories and feedback about specific programs.
  4. Is there a specific industry or specialty area that you want to pursue within data analytics? If so, read job descriptions and make sure that the bootcamp you choose teaches the skills and programs needed.

It’s always good to research job titles and possible employers even before starting a program. Data analytics jobs are not one-size-fits-all. To learn what kind of job options are available for data analytics bootcamp graduates, check out four possible career paths below.

Top 4 Careers To Pursue After a Data Analytics Bootcamp

Every kind of business needs data analytics to gather, clean, and interpret data and provide visualizations for decision-makers. The most common job title you’ll see is—no surprise here—data analyst.

Data analyst is the generalist title that many companies use for analyst roles, though the exact responsibilities vary. Some companies use the junior data analyst or senior data analyst, signaling the role’s seniority. You may also see jobs like “Data Analyst I” or “Operational Analyst IV,” indicating different pay grades with Roman numerals.

Beyond a generalist role, here are four data analyst specialties you should know about.

Business Analyst

Business analysts perform analyses to glean business intelligence – insights that help companies make decisions on revenue, marketing, or operations. You can find examples of this in both business-to-business (B2B) and business-to-consumer (B2C) organizations.

Let’s look at consumer products and services as an example. As more and more companies enroll customers in accounts and loyalty programs, they generate valuable data about customer purchases along with website and app activity. These companies need analysts to give insights into buying patterns so they can set competitive pricing and improve their performance and revenue.

Walmart, for example, claims to have the “world’s largest private database”. Walmart embeds data analytics positions within its merchandising, human resources, and technology teams to solve business challenges and improve outcomes.

Companies also house huge amounts of data within customer relationship management software (CRM) systems. Employers hire business analysts to support CRM administrators and marketing teams by creating dashboards and reports and validating data with SQL queries.  

In a B2B setting, a consulting company like PwC may hire a business analyst to conduct competitive intelligence, analyze a client’s customer data, or develop and test financial models. Business analysts need to have strong project management skills as they may conduct projects for multiple departments or external clients.

Financial Analyst

From interest rates to portfolio performance to underwriting, financial services is an industry built on data. It should be no surprise that banks, hedge funds, and insurance companies are one of the world’s biggest employers of data analysts and data scientists.

There are many reasons financial services companies invest in data analysis to improve their business. On one hand, they need to mitigate risk. By analyzing the past performance of loans and portfolios, they can make better decisions about future pricing and which investments they should keep or sell.

Fraud is also a huge issue, responsible for $4.7 billion in losses a year for companies. Access to real-time customer data can help financial services companies detect and prevent fraud.

Financial analysts need to have a strong mathematical and statistical background to land a job in addition to relevant programming languages.

Healthcare Data Analyst

Experts valued the healthcare analytics market at $8.4 billion in 2021 and expect it to grow 31% by 2027. The world of healthcare and medical data is exciting because it offers the chance to join in on solving huge global issues like epidemiology, improving patient experiences and outcomes, and finding life-altering medical breakthroughs.

Healthcare providers need data analysts to manage and interpret data in clinical trials and safeguard patient data according to HIPAA compliance. They will also need data analysts and scientists to contribute to emerging fields like AI in healthcare.

To get hired in a healthcare data analyst job, you need experience with databases such as SQL and Access and data visualization programs like Tableau. A general background in healthcare and an understanding of healthcare compliance is helpful, but not required.

Data Scientist

One excellent career path that data analysts can pursue is becoming a data scientist. Data analysts and data scientists are often lumped together, but they are in fact separate job functions.

Data scientists perform more complex, advanced data analysis than data analysts. While a data analyst interprets structured, historical data, a data scientist may analyze raw data from multiple sources to forecast future performance or behavior. Data analysts typically solve a known and specified problem, while data scientists may comb through big data for insights without knowing what they’re solving for. Data scientists are also integral in developing the latest AI and machine learning technology.

Because of their advanced skill set, data scientists earn more on average and have high job security based on job projections. You may not be able to land a data science job straight out of a data analytics bootcamp, but you can take the leap into data science with a few years of data analyst experience under your belt or with a data science bootcamp.

Job Hunting Success Tips After a Data Analytics Bootcamp

Once you’ve completed a data analytics bootcamp, you can start searching for data analyst entry-level jobs. Whether you’re interested in a large company, a startup, or a remote data analyst job, you’ll have many options. Bootcamp alumni have a lot of assets at their fingertips, from workforce-ready technical skills to networks of employers and alumni.

1. Display Your Certification on Your LinkedIn Profile and Resume

First, show off your credentials. Add your certification and badge if you have one to your LinkedIn profile and post about some of the things you learned in the bootcamp. Make sure to add your bootcamp and updated skills to your resume to make it shine.

2. Showcase Your Work in a Portfolio

The best data analytics bootcamps help students create a portfolio as part of the coursework. If you created one during the bootcamp, you won’t have much work to do other than adding the portfolio to your LinkedIn profile or a personal website if you have one.

If you haven’t created a portfolio yet, think about how to take one or two of your best projects and build a narrative around them. Show the problem you chose, how you overcame challenges, and what the results and business impact were. Make sure to include data visualizations to make it pop. Need ideas? You can browse GA student portfolios for inspiration. 

3. Use Career Services

Most bootcamps offer career services for free, so there’s no excuse not to take advantage of it. Work with career services to review your resume, help you prep for a technical interview, or negotiate a salary. Many bootcamps partner directly with employers (GA has 19,000 hiring partners around the globe) and can connect you with recruiters.

4. Tap Into Your Network

Even if you’re coming in as an outsider to data analytics, chances are that you’re better connected than you think. Reach out to anyone connected to data analytics or companies you’re interested in working for. Set up informational interviews and find out as much as you can about the industry and potential job openings.

Keep up with the cohort members from your bootcamp. You’re advocates, not competitors, for job openings and can support each other through the job search process.

How To Become a Data Analyst With No Experience

With up-to-date technical skills and a little grit, it’s completely possible to become a data analyst with no experience. Data analysts need to be good with numbers and have an attention to detail. Next, they need hands-on experience analyzing data in programs such as Python, Tableau, and SQL.

A data analytics bootcamp can equip anyone with the technical and soft skills they need to enter the data analytics job market. Whether you become a financial analyst, a healthcare analyst, or a business analyst, you can look forward to a fast-paced career on the cutting edge of technology and business evolution.

A good analyst is invaluable to companies, providing insights and observations that affect decision-making at the highest levels.

Ready to step into the gap?If you’re ready to explore all the job change options available after a data analytics bootcamp, fill out this short form to chat with our Admissions team. 

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