What Is a Financial Data Analyst?
Let's begin by comparing how a financial data analyst operates compared to other roles that have similar names. Bear in mind that while the financial data analyst role is a dedicated career path, the insights and advice included in this be helpful for a wide range of investment industry roles.
Data Analyst vs. Data Scientist
Financial data analysts and data scientists work with different types of data and exercise different specialized skills in their work. Data analysts are more likely to design financial reporting and compile investment insights to guide finance decision making. For this role, the ability to apply statistical methods to interpret a wide variety of existing data sets is key. Meanwhile, data scientists are more like data engineers. They are likely to have a computer programming background and to be involved in database design, developing data capture methods and building data pipelines to bring together disparate data points in a usable way. A simplified way to think about these roles is that data scientists build an infrastructure so that data analysts can access data and interpret it.
Data Analyst vs. Business Analyst
The differences between data analysts and business analysts (also called "business intelligence analysts") come down to the parts they play in business strategy. While data analysts organize and analyze financial data, business analysts turn the data that analysts report into data-driven business decisions. These might include budgeting, pricing, and planning related to a business's products or services.
Where these roles overlap is in their common fluency with financial data. You might see a financial data analyst and a business analyst working on projects together, using their specialties to solve business problems together.
Data Analyst vs. Financial Analyst
The job titles might sound similar, but financial data analysts and financial analysts — also called investment analysts — are not particularly similar roles. Financial analysts are money managers. They work as consultants with personal finance and corporate clients to develop individual investing strategies.
How to Become a Data Analyst
Looking for some pointers on how to become a successful data analyst? Entry-level financial data analyst positions will require a bachelor's degree, most often in a quantitative field like mathematics, computer science, economics, or business with a data analysis focus. If you are enrolled in a non-quantitative degree program, it may be harder to break into the data analyst career path without some additional training and experience to hone key skills. Elective courses to improve mathematical skills, data analysis internships, and/or finance field experiences may help you build enough financial data analyst skills to supplement a non-quantitative major and land an entry-level role.
More senior roles will require direct experience as a data analyst and strong knowledge of the finance industry and its regulatory environment. It should be possible to make the transition from a non-finance industry entry-level data analysis job to a finance industry role. You will need around 3-5 years as an entry-level data analyst, demonstrated financial background knowledge, and of course, stellar statistical skills including the ability to use common tools and software.
Here are a few areas we recommend working on to build your way toward the data analyst career path:
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Core Analytical & Technical Skills
- Statistical inference
- Financial modeling
- Database querying
- Data dashboard building
- Financial risk analysis
- Statistical programming languages
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Core Professional Skills
- Project management capabilities
- Cross-functional teamwork
- Leadership
- Interpersonal skills
- Communication skills
- Critical Thinking
- Workflow process management
Is a Data Analyst Career Right for Me?
On a day-to-day basis, data analysts have to be capable of working with both technology and people. Analytics jobs pivot between intensive statistical analysis, such as financial modeling, and soft skills, such as presenting data insights on a cross-functional project team, a key stakeholders' meeting, or a meeting with consulting clients. The ability to focus intently on interpreting data using sound statistical methods while also considering how the data can tell a story for an audience with a different area of expertise is crucial.
As with most industries, remote data analysis work is becoming increasingly available. Teamwork requirements should still be a core part of the job function, but the practicalities of how that teamwork is executed may look different across collaborative business software than it may have in a traditional office setting.
How to Become a Better Data Analyst
If you have strong analytics skills but want to improve your finance competencies, the CFA® Program is ideal for boosting investment analysis and portfolio management skills and demonstrating a commitment to ethics within the investment industry. We also offer the Certificate in Investment Performance Measurement (CIPM) program, which focuses more directly on business performance measurement.
In addition to professional certifications, you can always set the professional development goal of keeping up with current events in fintech, the intersection of finance and technology. This includes keeping up-to-date on topics like artificial intelligence in investment management and emerging trends like cryptocurrency.
Other Finance & Investment Management Career Tracks
Interested in exploring other financial services roles beyond financial data analyst? Check out more role descriptions, including:
How Can the CFA Program Help Me?
Data analysis in the investment industry is creating new opportunities for investment careers. In addition to roles that are directly involved with the investment process, there is also a growing demand for professionals who can apply their investment expertise to support the technology platforms and business models developed by technologists and others who lack investment training. The CFA Program provides the foundational knowledge of the investment industry to supplement and demonstrate how your background in data science is applicable within the world of finance.
Explore whether CFA Program is the right choice for your next career steps
