Evispot provides the financial industry with the decisions they need in the future – today. We do it by exploring artificial intelligence – because no human, neither configured software can handle the complexity of data that must be evaluated.
With 15 years of experience in the credit industry and a strong domain technology interest, we realized the opportunities AI entails in credit decisions. Traditional decisions models are based on a defined amount of parameters. A defined amount of parameters entail limited answers. The possibility to identify patterns, anomalies and multidimensional relationship has not been possible before – until now. The era of traditional credit models is over. New, constantly optimizing, models are the future.
WE + YOU
Evispot is looking for a machine learning engineer to join the team, to take part in the product- and technology development and creating excellent products for the financial industry. You will be a part of disrupting the financial industry and creating next generation credit decisions.
– Take part of Evispot current technology- and product development. – Develop solutions for real world, large scale problems. – Hands-on prototyping new algorithms, evaluate with experiments. – Also, productionize solutions at scale or/and plan for scaling. – Help drive optimization, testing and tooling to improve data quality. – Take part of an active start-up who constantly strives to create excellent products. – Work closely and collaborate with Evispot’s advisors with over 10 years of AI experience. – Evispot’s office is located in Gothenburg, Sweden. – Flexible hours and all other startup-related clichés you might desire.
– Background and experience in machine learning or a related field. – Experience of feature engineering and prototyping machine learning applications, that have been deployed to production – You are well-versed in programming and scripting (not only R and Matlab) – Experience implementing machine learning systems in Python and R. – You care about agile software processes, data-driven development, reliability, and disciplined experimentation – Grit, and a true problem-solving mindset – You are excited about joining a startup environment where anything & everything is happening at once.
We are living in the data age. Every device around us is constantly assessing, calculating and interacting – resulting in enormous amounts of data constantly being created. The term big data has been frequently used during the last decade. The term is used to describe the collection and analysis of data on a scale or of a complexity that makes the use of data challenging. Extracting insights and value of these massive datasets is challenging, but when done properly you will find yourself increasingly efficient.
The UK house of commons wrote a study named The big data dilemma on the massive increase of data. The study highlights the importance of taking action and using the data to create valuable insights for your business. To add some perspective: in 2014 204 million emails were sent and every minute 4 million Google search queries were done. Even more astonishing is that 90% of the data currently in the world was created in the last two years and the amount of global data is predicted to grow 40% year on year for the next decade.
– So what can you do?
The credit scoring giant Experian believes the role of big data in financial service is huge, naming fraud detection and general ledger data to gain previously impossible insights as some of many of possible products. Experian states that enabling ‘real time’ data-decisions is the difference between winners and losers in the financial markets.
This data explosion offers a great opportunity of understanding your environment and peers on a deeper level. Properly exploited, this data should be transformative, increasing efficiency, unlocking new avenues in life-saving research and creating yet unimagined opportunities for innovation. However, the current datasets are nowhere near fully exploited despite research showing that data-driven companies being 10% more productive than those that do not operationalise on their data. Today an estimated 12% of all data analysed, meaning there is yet much to explore. – Extracting insight and value from these massive data sets is difficult, but when done properly it can be the difference between winning and losing. Evispot was founded on the mission of being experts of insight-extraction in the data age.
Want to learn more about how your business can benefit from data? Check out the Evi-LAB – our environment for insight extraction.