Working as Data Scientists, we have to solve various problems on a daily basis. Some of them are tasks we've completed many times before and some of them are completely new to us and we have to understand the business logic behind them before starting building models. The latter was the case when our client, a bank, approached us a couple of months ago with a problem they were tackling – whether to provide or deny loans to gamblers.
Although our daily job is to help companies with setting up their analytics processes, building machine learning solutions, and hiring data scientists, we never say no to a hackathon invitation. Recently, we participated in one exciting hackathon in Slovakia, so we decided to share our experience while it's still fresh in our memories.
In this month's blog post, we are going to share a case study based on a project we did for one of our clients – a Slovak bank.
By now, most financial institutions have been familiar with data analysis for some time. One use case for examples is credit scoring. Money lenders, such as banks and credit card companies, have been using it for a couple of decades now to evaluate the risk of lending money to consumers and to mitigate losses. However, the recent arrival of new technologies and the rise of machine learning and Data Science brought along many new opportunities.
Whether you are from a startup or a big corporation, every company today has one problem in common. At some point, there is a need to develop your own analytic capabilities so you can leverage your data efficiently. While outsourcing and getting help from consultants can be a great way to get things off the ground, eventually it does make sense to have the dedicated people in-house. And voila, you are searching for your first Data Scientist.
In this blog post, we will take a look at the activity on websites that became a significant part of development across all areas in, as well as, outside of Data Science: GitHub and StackOverflow. It doesn't matter where developers are from or what their specific focus is, everyone uses these websites.
Gut feeling used to be the biggest asset of successful businessmen in the past. Nowadays, intuition still plays an important role, but with all the available knowledge and technologies, there has been a significant shift. One of the most important sources of a competitive advantage these days is data. Big Data is a hype and undoubtedly a bandwagon to jump on. But how?
For this blog post we decided to jump on the PokémonGO hype and add a bit of science into the craze. Our goal is to give you the optimal portfolio of Pokémon to train, so you can be as effective as possible against a wide variety of opponents. As each Pokémon has its strengths and weaknesses, we created clusters of Pokémon with similar characteristics and looked at the few selected ones allowing the player to compete against as many different enemies as possible.
In the next blog of our Knoyd series, we are going to show one of the ways of measuring impact of NBA players on the game. Everyone knows that all-stars like LeBron James or Stephen Curry have tremendous impact and they show it in every game on the floor. However, very often role players need to step up and save the game. This analysis is dedicated especially to these players and how they can change the game by their performance. The cornerstone of this analysis is the basic correlation between players‘ impact and result of the game. The way, how impact of an individual player is computed, will be described later on.