Financial Analyst ML Training

Challenge

Our client faced the challenge of designing a foundational training program for data analysis and the use of AI in the company's finance sector. The goal was to provide a general overview of typical data analysis tools and classic use cases of automation and machine learning methods. Additionally, a common vocabulary and shared objectives were to be developed for communication between data experts and domain experts within the company.

Approach

In an eight-week agile development process, we designed a six-part training program in collaboration with our client. The focus was on the interactive exploration of core analytical concepts and guided use case ideation. The aim was to enable participants to independently explore possible applications of AI and data analysis tools and to communicate their goals and requirements adequately to technical experts.

In the statworx cloud, machine learning playgrounds and peer learning challenges were provided for interactive experimentation, with the goal of offering a cost-effective and flexibly scalable backend for large numbers of users. Learners had the opportunity to set their own content priorities in constructivist learning environments, even with little theoretical prior knowledge, in a practical and independent manner.

Result

Through our training concept, over 120 people at multiple company locations have already been trained. Both remote and in-person training supported many networks and the initial ideation of projects. The training serves as a starting point for a larger training initiative, allowing modules on specialized topics to be added to the financial analyst training track.