Almost done with your study and looking for a place to write your thesis? Consider Veneficus! When working on our projects, you get to see the practical applications of data science right away. At Veneficus, we have several subjects we want to research further. For most of them we have data available which means you start right away.
Writing your thesis at Veneficus does not only give you the opportunity to take on a challenging project, you can also get a close look of how we work as a company. While working on your thesis, you will support our "regular" projects as well, if you want. This gives you a sense of what it would be like to work for Veneficus.
Veneficus consists of a team of data scientists, developers and engineers with a passion for data. Our primary goal is to deliver innovative and understandable insights to grow our clients. To achieve this, we deploy the online platform developed by ourselves. We focus on the following sectors:
- Retail & E-commerce
- Real Estate
- Public Sector
We think in terms of solutions and have a fresh, innovative view of the field. Our clients love our passionate approach and the successful results we achieve. We are eager to learn, always try out new stuff and also dare to make mistakes. But is is not all about algorithms, tools and advise. We like to alternate racking our brain over complex issues with playing a game of foosball.
The thesis topics we are interested in range across the ones mentioned below. If you have an interesting idea for a project you want to take on, let us know. If not, below are some topics we would like to see researched.
Companies have a lot of ways to spend their marketing/media budget. They can for example send email campaigns, air tv commercials or buy Google Adwords. Most of our clients don't know the optimal way to divide their budget over these media channels.
The biggest challenge is related to indirect effects. Someone might see an online add, check the website for information and decide to buy it a week later in a real store (ROPO, Research Online, Purchase Offline). And how to measure the combined effects of TV commercials, online ads and paper folder campaigns running side-by-side?
We are currently using a Bayesian model to measure the effects in which we include long-term Adstock effects. The next step would be to use optimization methods to get to the optimal spend strategy over all these channels. This would be the main topic of your thesis on media effectiveness.
Recommender systems, also called recommender engines, are an increasingly hot topic in data science nowadays. They are used by all major companies: YouTube uses them to select the next video to play and Facebook to propose new potential friends. The ability to propose the right things to the right people at the right time would be a huge business advantage to any company. For this reason, many companies invest heavily in recommender systems. Netflix, for instance, has offered a million dollars prize back in 2009 for anyone who improves their existing system by 10%!
In the marketing domain, recommender systems are used to personalize offers for the customers. This can be appraoched in a number of ways. One is to cluster similar clients together and propose to each of them products in which the other members of the cluster were interested. The other is to group similar products, and based on their characteristics try to estimate why kind of product the client might like.
R has a couple of packages for building recommender systems. Most of them, however, focus on one particular approach. The topic of the thesis would be build one generic framework, possibly in form of an R package, that combines or extends existing methods for suggesting recommendations in the retail and e-commerce markets.
Explain efficiency scores in location potential analysis for retailers
At Veneficus we perform location analysis for our retail clients. For this analysis we use data about demographics and competition to assign a potential revenue for each store location. Using this, the revenues of different stores can be compared more objectively.
On top of this potential per store, the model output contains information about which variables drive the potential (positively or negatively). However there is discussion about the method used for this. Does it yield unbiased and efficient estimators?
The aim of this project is to research and gain understanding of these estimators, in order to know whether we can trust them. If this turns out not to be the case, there should be alternatives to obtain a good description of what drives potential.
Risk assessment of insurances
Insurance companies create risk profiles for their customers. These profiles are usually generic, while in theory, it is possible to make a more precise risk profile for a specific group of customers. The goal of this project will be to obtain more specific risk profiles. First, customers can be clustered, using several variables like age, education level, income, and many more. After the clusters are obtained, a risk profile can be assigned to each cluster, and hence to each individual. These risk profiles will be more specific and more realistic, allowing the insurance company to make a better assessment of future costs.
Are you interested in doing research at Veneficus? Do you like a challenge? If so, please send your resume and cover letter to email@example.com. Would you like to know more about Veneficus and this position, please contact Jan-Willem via +31 6 - 21 91 82 49.