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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 whilethe financial data analyst role is a dedicatedcareer 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 scientistswork 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 currently work as a junior data analyst but want to set some professional development goals to help yourself improve, we recommend exploring professional certifications. This approach will allow you to develop in a structured setting with a demonstrated end product that you can leverage when advocating for career advancement in your organization.
If you have strong analytics skills but want to improve your finance competencies, the CFA® Programis 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:
- Data scientist
- Research analyst
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
As a seasoned expert in the field of data analysis and financial analytics, I have a wealth of knowledge and practical experience that positions me well to discuss the concepts presented in the article on Privacy Settings and the role of a Financial Data Analyst.
Data Analyst vs. Data Scientist: The article rightly distinguishes between data analysts and data scientists, highlighting the different types of data they work with and their specialized skills. A financial data analyst focuses on designing financial reporting and compiling investment insights to guide decision-making in the finance sector. In contrast, data scientists are portrayed as building the infrastructure that allows data analysts to access and interpret data, often involving computer programming, database design, and developing data capture methods.
Data Analyst vs. Business Analyst: The article goes on to discuss the distinctions between data analysts and business analysts, emphasizing their roles in business strategy. While data analysts organize and analyze financial data, business analysts convert this data into actionable business decisions, such as budgeting, pricing, and planning. The common fluency with financial data is highlighted, showcasing how these roles can collaborate on projects to solve business problems.
Data Analyst vs. Financial Analyst: The article clarifies the differences between financial data analysts and financial analysts (or investment analysts). Financial analysts are depicted as money managers, working closely with personal finance and corporate clients to develop individual investment strategies. This distinction is crucial in understanding the unique responsibilities and focus areas of each role.
How to Become a Data Analyst: For individuals aspiring to become data analysts, the article provides valuable insights into the educational requirements and career path. It emphasizes the need for a bachelor's degree, preferably in a quantitative field, and recommends additional training and experience for those with non-quantitative degrees. The progression from entry-level to senior roles is outlined, highlighting the importance of direct experience, financial knowledge, and statistical skills.
Core Analytical & Technical Skills and Core Professional Skills: The article lists essential skills for aspiring data analysts, categorizing them into core analytical and technical skills and core professional skills. These include statistical inference, financial modeling, database querying, project management, leadership, interpersonal skills, communication skills, critical thinking, and workflow process management. This comprehensive overview underscores the multifaceted nature of the data analyst role.
Is a Data Analyst Career Right for Me? The article delves into the day-to-day responsibilities of data analysts, emphasizing the need for a balance between technology and interpersonal skills. It discusses the growing trend of remote data analysis work and highlights the importance of teamwork in a virtual environment.
How to Become a Better Data Analyst: For junior data analysts looking to improve, the article recommends exploring professional certifications and setting professional development goals. The CFA® Program is suggested for enhancing investment analysis and portfolio management skills, demonstrating a commitment to ethics in the investment industry. Staying updated on current events in fintech and related topics, such as artificial intelligence and cryptocurrency, is also encouraged.
Other Finance & Investment Management Career Tracks: The article concludes by suggesting alternative career tracks in the finance and investment management field, including roles such as data scientist and research analyst.
In summary, the article provides a comprehensive overview of the financial data analyst role, comparing it to related positions, outlining the required skills, educational paths, and avenues for professional development within the finance industry.
