How to Change Your Career from Finance to Data Science

Data science is a highly rewarding field that is growing in popularity, as more organisations look to reinforce their operations with empirical insights. If you currently work in the finance industry, you may already be familiar with many of the core data science skills, which could accelerate your transition to a new career path. 

With Lumify Learn’s range of online IT courses, you can upskill into a data science role. Study business analyst courses and certifications that prepare you with the skills and knowledge you need in order to complete your transition into this increasingly popular industry.

Data Science vs Finance: How They Overlap

The data science skill set is heavily grounded in statistical analysis and other mathematical concepts that will be familiar to professionals in the financial sector. In fact, you may find that you are already using data science in the finance industry, to analyse trends and make predictions for future growth. Below, we have listed a number of specific transferrable skills between data science and finance.

• Strong knowledge of mathematics

Both data science and finance rely heavily on concepts of mathematics to perform calculations and algebraic operations. Finance professionals already use these skills in many of their daily tasks, enabling them to adapt to the various demands of a data science role.

• Familiarity with statistics and data interpretation

Many data science professionals have a qualification in statistical analysis, as it is a fundamental aspect of their job. Working with statistics and data is a common skill required in both finance and data science, providing a significant advantage to applicants transitioning between these two industries.

• Analytical skills

In both the financial and data science industries, it is crucial to be able to understand and interpret information in order to solve complex issues. Insights from data analysis in the finance industry can also be utilised in data science roles to aid in the decision-making process.

• Proficiency in data visualisation

In both finance and data science, identifying trends in data and presenting them in the most effective way is crucial. Where finance professionals use data visualisation to present reports and findings, the same skills are utilised in data science to identify patterns in models.

• Risk management and mitigation

Risk management is a term common to both finance and data science professionals. The same skills used to determine a credit rating or identify threats in a portfolio can be used to cautiously model predictions and analyse possible scenarios as a data analyst.

Core Data Science Skills to Develop

If you are looking to transition from a career in finance to a data science role, there are a number of skills you may need to develop. With Lumify Learn’s business analyst courses, you can fill in any knowledge or skill gaps in your resume, to build a convincing application for a range of data science roles.

• Programming languages

Programming languages such as Python, R and SQL are critical knowledge for data science professionals. Depending on your specialisation in finance, you may need to study an additional course to learn these programming languages before changing career paths.

• Data visualisation

For those finance professionals whose roles do not extend to arranging data visually, a certification in this area should form part of your data science training. Data visualisation is a powerful communication tool which is used throughout the industry, as it helps to make technical information more digestible.

• Cloud computing

Many data science roles use scalable cloud computing infrastructure solutions, such as AWS, Google Cloud or Microsoft Azure. One of our cloud computing courses can help you learn how to use these programs to their full potential in your new data science role. 

Data Science Qualifications: Tips for Finance Professionals

Finance professionals are at a major advantage when transitioning to data science, as they already have real-world experience working with many of their new industry’s key concepts. However, there are still some data science qualifications that are worth attaining before applying for your first industry role.

• Master’s degrees

Depending on the data science role you are interested in, and your previous education, a master’s degree may be a worthwhile investment as part of your career transition. These degrees provide a comprehensive understanding of data science theory, adequately equipping you for the next step in your career.

• Online certifications and bootcamps

For many finance professionals looking to transition into data science, an online bootcamp or certification will be helpful in landing your first industry role. From upskilling to a more general overview of the industry, these courses fill in any knowledge gaps prior to completing your career move.

• Technical courses

A technical course is another popular option for finance professionals looking to transition to a career in data science. These courses typically focus on learning a particular skill or program for a specific job, and can be studied after you have been hired in the role. 

Transition to Data Science with Lumify Learn

Data science and finance share more common ground than many people realise, both requiring advanced knowledge of mathematics, statistical analysis and risk management. Any knowledge gaps can easily be rectified by studying any of our data science qualifications, from technical courses to certifications and master’s degrees.

Lumify Learn’s range of data analyst certifications assist professionals from a range of industries, including finance, to transition to a new career path. Our data science qualifications are delivered online through flexible study plans, enabling you to fit your studies around your personal schedule. Browse our courses today and discover how you can leverage your previous experience in finance to become a data analyst.