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As FinTech revolutionizes the financial world, it also creates significant job opportunities for technology professionals with the right skills.

Some of the use cases for technology in the financial world involve improving the customer service process. While automated chatbots garner a significant amount of attention, WealthTech or robo-advisors take that concept to another level.

Robo-advisors essentially serve as automated financial planners, helping clients manage their investment portfolios. IT professionals with experience in AI, data analysis, and software engineering boast the in-demand skills for creating robo-advisory systems. Here’s a closer look at a FinTech concept pundits identify as one offering excellent prospects for a rewarding career.

What Career Opportunities Are There Around Robo-Advisory Systems?

A High-Level Overview of Robo-Advisory Technology

Simply stated, robo-advisory systems combine a chatbot with an automated real-time financial analysis service usually provided over the Cloud. AI plays a crucial role in both components of a robo-advisory application. Generative AI, similar to ChatGPT, leverages its large language models to interpret user queries and compose appropriate textual responses. Machine learning works on the back end, performing real-time data analysis of client portfolios and the current market status.

The benefits of robo-advisory tech to financial institutions share similarities with other use-cases for AI and automation. Most importantly, using automated robo-advisors frees up human financial planners to work on more value-added tasks. In fact, most robo-advisory systems include the ability to speak with a human financial planner when necessary. All told, leveraging robo-advisors helps financial institutions provide better customer service and generate more business.

The Market For Robo-Advisory Systems Continues to Expand

A recent analysis of various niches within FinTech identify robo-advisory technology as one with excellent career prospects. In fact, they predict this market to grow by 25 to 30 percent on an annual basis. Needless to say, expect a multitude of job opportunities crafting robo-advisory systems throughout the rest of the decade.

The Technical Skills You Need to Build Robo-Advisory Applications

As highlighted above, robo-advisory systems rely on AI and machine learning, so experience building ML models is a must. Additionally, exposure to generative AI and large language models also remains critical. An automated robo-advisor needs to understand customer requests and provide meaningful responses in any conversation with clients.

Additionally, companies building robo-advisory applications want software engineers experienced in data analytics and data engineering. A history of building and training machine learning models for this purpose also identifies the top candidates.

Looking for a New Job?

If you are interested in IT job opportunities in FinTech, contact the expert recruiters at The CERES Group. As one of the top technical staffing agencies in New England, we know the companies looking for exceptional candidates. Connect with us as soon as possible!

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