Data science and artificial intelligence are becoming increasingly important in all areas of the economy and our daily lives. Many companies are just taking their first steps in this direction, while others have already moved beyond the pilot project phase and are facing major roll-outs. What most of these companies have in common is that they do not yet have sufficient in-house expertise in this complex field, and the relevant specialists are very difficult to find on the labour market.

This is where KPMG's Lighthouse data science programme comes in.

The Lighthouse team covers all aspects of data science and artificial intelligence. Most of our data scientists have a degree in maths, computer science, physics or similar subjects and therefore have a deep understanding of data science methods. Together with the technical expertise of colleagues from other departments at KPMG, solutions are created that combine technical excellence and practical relevance.

Data Science Academy and Data Science Factory

The Data Science Academy offers a wide range of training programmes in the field of data science. This starts with general introductions to the topic, but also includes deep dives into specialised topics such as deep learning and natural language processing for mathematical and technical target groups. We offer our experts' own courses as well as curating the offerings of numerous online service providers and tailoring them to the individual needs of our customers.

In addition to these more practically orientated offers, the C-level seminars provide an overview for decision-makers. In particular, we categorise the various technologies in terms of their market maturity and practical relevance and discuss the impact on different industries and their business models.

The Data Science Factory stands for the industrialisation of data science. The aim here is to organise the individual phases in the life cycle of a data science or AI application from the specification of the use case to the operational implementation in a software system in a standardised manner and to enable the customer to outsource this process (in full or in part). Our experts take on the roles that cannot be filled by the customer and integrate seamlessly into the overall process. This can also include cyclical repetition or permanent operation.

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Standard solutions

The experience gained from numerous data science projects has resulted in largely standardised solutions for certain issues, which can be adapted to the customer's specific situation with little effort. These include, for example

Intelligent Pricing, a system for optimising pricing in B2B,
Geo Analytics, a tool for analysing traffic flows and evaluating locations,
ScanDoc, a system for extracting information from (partially) structured documents, which is used, for example, to automate invoice recognition and booking.

Special Projects

The data science team also focuses on projects to solve highly specialised tasks. These relate to almost all sectors such as the insurance industry, wholesale and retail, logistics, production, etc. and deal with problems such as

the optimisation of spare parts logistics for technical services
supporting work in call centres through the use of artificial intelligence
the prediction of customer behaviour,
analysing sensor data to support predictive maintenance in the area of Industry 4.0,
setting up a semantic search for large volumes of documents,
extracting information from continuous text,

to name just a few. Depending on the complexity of the task, we use statistical and mathematical modelling techniques as well as machine learning and deep learning. We endeavour to select the most suitable technique in each case to optimise the cost-benefit ratio.

Our data scientists and developers are proficient in all common tools and languages and are able to respond to the customer's specific requirements with regard to the system environment.

Data Science at KPMG's Lighthouse thus stands for a comprehensive range of services from training and the use of standardised tools to the implementation of specialised projects, the development and operation of intelligent systems and the auditing and development of AI governance.

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