Bridging the financial industry’s data skills gap with software

A recent study by 365 Data Science found that in-demand data scientists change employers every 1.7 years on average. And developers are also quick to change jobs. A February 2022 survey conducted by Salesforce’s Mulesoft found that 93% of 600 enterprise IT managers in the US, UK, France, Germany and Australia had more difficulty retaining qualified developers and 86% had also more difficult to recruit since the start of the pandemic.

This is a big problem for financial services companies, as business processes are increasingly data-intensive. To avoid drowning in data, businesses need to digitize and become more data-driven and they depend on expert technology and data scientists to provide this capability.

Provide technologies and tools

Every data scientist and developer wants to be paid well for what they do, but they also need a stimulating work environment and the ability to work on interesting problems using cutting-edge technology. In addition, they want their jobs to allow them to develop their skills and advance their careers. In addition, each work environment should be supported by an appropriate cloud infrastructure allowing easy and fast data integration and sharing, as well as the use of the latest open source technologies, which give data experts the creative freedom and the processing power needed to experiment with different scenarios. .

Many financial services organizations still fail to make the latest technology available to these employees. Recent search by Alveo in the UK, US and Asia, which focused on analyzing ESG data, specifically reveals that only 37% of data scientists at financial services companies are currently using AI, l learning and other advanced technologies in their core analytical and investment processes and workflows. This underscores the fact that, despite the potential of AI and its rapid growth, harnessing its capability for practical purposes can be more challenging.

Why data scientists and developers need to be stretched

Many data scientists working for financial services companies are burdened with basic and/or routine administrative tasks. Two-thirds (66%) of respondents to the Alveo survey say that quants and data analysts in their organization need to spend between 25% and 50% of their time collecting, preparing and checking the quality of data.

Even though they are to be well paid for their efforts, most data scientists will not want to work in roles where they spend their time dealing with basic data aggregation and quality control issues rather than inferring new information and performing statistical analyzes on large data sets. Getting bogged down in office work will prevent staff from developing the skills and abilities they need to advance their careers and keep them motivated. Integrated data management and analytics solutions, as well as data modeling, quality and integration capabilities, will enable staff to be operational.

Training and the wider working environment

From the perspective of the financial services company, this enhanced technological capability must be accompanied by relevant training. It’s often a critical way to engage and retain these important workers.

It also plays into the need to create a flexible environment in which developers and data scientists can work. This may include offering hybrid working arrangements and allowing staff to work remotely if necessary. Developers, in particular, appreciate working in a calm, quiet place that allows them to focus their attention on their creative work. It is important here to ensure that the home-work environment is safe and that staff have what they need to work as efficiently as possible.

Suggest a challenge

It is also essential to ensure that these staff are supported in the use of popular and widely used technologies like Cassandra and Apache Spark: technologies that, once learned by data scientists, can become portable skills. For data scientists, the equivalent is probably the latest productivity tool, which allows them to access complex analytical tasks as quickly as possible, skipping the more mundane data collection, mastering and analysis tasks. ‘aggregation.

Highly skilled and trained developers and data scientists should have the freedom to work in the way that works best for them. It should be a collaborative process, probably involving brainstorming sessions with colleagues, but there should always be an element of unleashing the creativity of your analysts and development experts.

Financial services firms can further accelerate the engagement of data scientists and developers by ensuring these employees are capable of working on challenging projects with interesting and game-changing clients: the kind that drive them to work hard and realize their full potential.

EEnabling associates to hone these skills serving demanding high-end clients, from central banks to major hedge funds, will help their development. Thus, companies can counter The big resignationkeep data scientists and developers engaged longer, develop their skills to position them well in their long-term careers, and reap other rewards in terms of efficient project execution and increased customer engagement.

About the Author: Martijn Groot is Vice President of Marketing and Strategy at Alveo.

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