The different types of analysts you can become in 2025

The growing demand for Data Analysts in 2025

In today’s technologically savvy world, there is an increasing reliance on data and insights when it comes to decision-making. Although leveraging analytics was previously something only attributed to tech companies, nowadays, organizations of all kinds are tapping into the power of data: whether it’s healthcare, finance, or e-commerce, the culture of making data-driven decisions now spans a variety of different industries.

This is all the more prevalent with the impact of artificial intelligence (AI) and automation, which has also had an impact on analytics professionals as a whole. As data analysts are beginning to spend more time extracting meaningful insights rather than simply crunching numbers, there has been a growing demand for skilled Data Analysts.

As mentioned though, Analysts are needed both in the tech world and beyond, so there are many different avenues you can take if this field interests you. This article will walk you through a number of Data Analyst career pathways and will provide some tips and tricks for choosing the right one. We’ll also go through some future trends in Data Analytics and tell you how you can get ahead of the curve and jump-start your career.

8 different types of Analysts you can become in 2025

1. Data Analyst

• What they do: Data Analysts work with a variety of datasets to generate insights for business decisions. This is the most common type of Data Analyst.
  
• Industries they work in: Tech, retail, finance, marketing, and healthcare
  
• Key skills/tools needed: SQL, Python, Excel, Tableau, and Power BI.
  
• Average salary range: About $64,000 per year in 2025.
  
• Career progression opportunities: Senior Data Analyst, Data Scientist.

2. Business Intelligence (BI) Analyst

• What they do: BI Analysts focus on turning raw data into actionable business insights through dashboards and reports.
  
• Industries they work in: Corporate strategy, e-commerce, manufacturing, logistics.
  
• Key skills and tools: Data visualization, database management, business strategy, Tableau, Power BI.
  
• Average salary range: About $69,032 per year in 2025.
  
• Career progression opportunities: Senior BI Analyst, BI Manager/Director.

3. Marketing Analyst

• What they do: Marketing Analysts specialize in analyzing consumer behaviour, digital marketing campaigns, and sales performance.
  
• Industries they work in: Digital marketing, e-commerce, social media, advertising.
  
• Key skills and tools: Google Analytics, SEO, A/B testing, customer segmentation.
  
• Average salary range: About $67,667 per year in 2025.
  
• Career progression opportunities: Senior Marketing Analyst, Marketing Analytics Manager

4. Financial Analyst

• What they do: Financial Analysts work with financial modelling, risk assessment, and investment data to help businesses make informed financial decisions.
  
• Industries they work in: Banking, fintech, investment firms, insurance.
  
• Key skills and tools: Excel, SQL, financial modelling, risk analysis.
  
• Average salary range: About $63,028 per year in 2025.
  
• Career progression opportunities: Investment Analyst, Senior Financial Analyst, Finance Manager

5. Healthcare Analyst

• What they do: Healthcare Analysts analyze patient data, operational efficiencies, and healthcare trends to improve medical outcomes and cost efficiency.
  
• Industries they work in: Hospitals, insurance, biotech, pharmaceuticals.
  
• Key skills and tools: SQL, Python, EHR systems, HIPAA compliance, predictive modelling.
  
• Average salary range: About $57,128 per year in 2025.
  
• Career progression opportunities: Senior Healthcare Analyst, Healthcare Analytics Manager

6. AI & Machine Learning Analyst

• What they do: AI & Machine Learning Analysts focus on analyzing AI models, training datasets, and ensuring accuracy in machine learning predictions.
  
• Industries they work in: Tech, finance, autonomous systems, AI-driven marketing.
  
• Key skills and tools: Python, TensorFlow, machine learning algorithms, AI ethics.
  
• Average salary range: About $96,071 per year in 2025.
  
• Career progression opportunities: Machine Learning Engineer, Senior Data Scientist

7. Cybersecurity Data Analyst

• What they do: They use data analysis to detect, prevent, and respond to cyber threats and security breaches.
  
• Industries they work in: Government, banking, IT security, cloud computing.
  
• Key skills and tools: Network security, penetration testing, threat intelligence, anomaly detection.
  
• Average salary range: About $64,096 per year in 2025.
  
• Career progression opportunities: Senior Cybersecurity Analyst, Senior Operations Center (SOC) Manager, Chief Information Officer.

8. Supply Chain & Operations Analyst

• What they do: Supply Chain & Operations Analysts focus on optimizing logistics, inventory management, and operational efficiencies through data-driven insights.
  
• Industries they work in: Manufacturing, retail, transportation, e-commerce.
  
• Key skills and tools: ERP systems, forecasting models, supply chain analytics tools.
  
• Average salary range: About $57,658 per year in 2025.
  
• Career progression opportunities: Senior Supply Chain Analyst, Supply Chain Manager, Director of Operations

How to choose the right Data Analyst career path

With so many different types of Data Analysts, it can definitely be overwhelming or intimidating to choose just one of these avenues. Not to worry, though: there are lots of strategies for picking the best fit for you. It’s also worth mentioning that a career in Data Analytics is dynamic and constantly evolving, so you can always pivot or shift your path down the line.

To begin, it might be helpful to complete a self-assessment to evaluate how your existing skills, interests, and industry preferences match up with the different career paths. For example, if you have a personal interest in medicine, health, or wellness, the Healthcare Analyst path could be a good way to incorporate your passion into your career.

As a next step, take a look at the required education and certifications for each of the different Analyst roles. This might help you understand how much time, effort or financial resources are required of each, which you can then align with your own unique priorities.

For example, from an education perspective, there are many different ways to become a Data Analyst: you can take a more traditional academic path and go to university or college, you can choose to self-study and go at your own pace, or you can sign up for an online bootcamp like the one at Lighthouse Labs.

Finally, it’s important to consider career growth potential and future job outlook. If professional development is important to you, you might want to pick a Data Analyst career pathway that has lots of room for upward mobility. For example, AI and Machine Learning are particularly top of mind in 2025, this could be one of the best career paths in data analytics as it is the most lucrative.

Future trends in Data Analytics careers (2025 & beyond)

As mentioned, the increasing role of AI and automation in analytics is playing a large role in the field as a whole. Due to this, AI and machine learning Data Analyst jobs have definitely been on the rise and are seeing higher demand. As all Data Analytics careers continue to develop, it’s important to keep an eye on trends that might have an impact on different Data Analysts' roles.

For example, we have seen a recent emergence in hybrid roles, such as AI Ethics Data Analyst or ESG Data Analyst. These kinds of Data Analysts can still apply to any industry, but they are particularly focused on the ethical use of data within an organization.

There has also been a particular demand for real-time data analysis and cloud-based analytics. As organizations continue to rely on data to make important business decisions, they are also cognizant of the rapid pace of our technological world.

The speed at which these organizations want to implement improvements and optimize performance has never been faster. With the increased ease at which we can access data these days, there is an element of maintaining a competitive edge that comes into play.

The role of cloud-based analytics is also becoming more and more important for Data Analysts anywhere to be able to access raw data. As our world continues to embrace hybrid and remote work, cloud-based systems allow for improved security, access and overall collaboration.

Jump-start your career today

If you have an idea of which Data Analyst career path you’re most interested in, you can begin to explore courses, bootcamps, or certifications based on your choice. There may be specific data analytics programs that focus more narrowly on your area of interest, whether it be healthcare or finance. You can also consider pursuing a more generalized degree in these fields first to give yourself a foundational base to build upon.

No matter which pathway you pick, though, Lighthouse Labs offers a Data Analytics Bootcamp that will give you the skills and knowledge to become any kind of Data Analyst. Our program can help you launch your career in data analytics in just 8 or 18 weeks and is available fully online for your convenience. Download our curriculum today to learn more about the bootcamp!

If you want to keep improving your skills, there are also so many resources available online. The best part is that many of these are free! Check out the list below:

• Lighthouse Labs SQL Essentials Bundle: Make your way through five beginner-friendly, video-led courses with practical, hands-on, real-world examples to build a solid foundation in SQL and boost your confidence working with data.
  
• Google’s Data Analytics Certificate: For a guided introduction to data analytics fundamentals, Google’s Data Analytics Certificate is an excellent starting point. Created by industry experts, this program establishes a robust foundation for aspiring Data Analysts. Dive into comprehensive data analysis techniques, adeptly visualize insights, and master essential tools. It accommodates those who prefer structured, guided learning approaches.
  
• FreeCodeCamp’s Data Analysis with Python: New to the realm of data analytics? FreeCodeCamp's Data Analysis with Python is a comprehensive resource for beginners. With hands-on practice and practical exercises, it aids in acquiring proficiency in data manipulation and visualization using Python. This resource caters to learners who thrive on practical exercises and are looking to grasp the basics of data analytics.
  
• Data Camp: Built on a hands-on learning style, Data Camp elevates your data manipulation, visualization, and statistical skills. Ideal for practical learners, it grants you valuable experience in the data analytics field. By engaging with real-world scenarios, this resource is tailored for those who prefer a hands-on approach to learning data analytics.

Finally, we also invite you to connect with professionals or join communities for career guidance. Talking to Data Analysts from a variety of fields can give you insights into their real-life experiences and how their day-to-day work varies. As well, meeting with like-minded data analytics professionals will not only expand your network but can also open doors to more career opportunities down the line.

When completing a program at Lighthouse Labs, you get access to our community of alumni so you can continue to learn, connect and grow with one another. So what are you waiting for? Enroll in our Data Analytics Bootcamp today!