LeanIX aspires to become the number one SaaS solution to modernize IT architectures. And we are on a good way. Hundreds of well-known brands like adidas, Zalando, and Vodafone make better decisions in IT with LeanIX.
But LeanIX is not just the product, so it's a great place to work. Colleagues from various countries make our vision reality. Yes, we have to work hard to achieve our ambitious goals. But we have everything to do so. We have invested a lot in a working environment that allows everyone to thrive. We believe in open access to leadership, transparent communication, personal development, a modern air-working environment and world-class teams.
We are looking for a Data Scientist that wants to help us discover the information hidden in vast amounts of data, and help us make smarter. Your primary focus wants to be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. Key objective is to improve and extend the use of automated internal A / B testing procedures.
WHAT IS WAITING FOR YOU?
- Selecting features, building and optimizing machine learning models
- Data mining using state-of-the-art methods
- Extending company's data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant to building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Doing ad hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
WHAT ARE WE LOOKING FOR?
- Excellent understanding of machine learning techniques and algorithms, such as Artificial Neural Networks, SVM, Random Forests, etc.
- Experience with common data science toolkits, such as Python, sklearn, PyTorch, Tensorflow / Keras, etc.
- Great communication skills
- Experience with data visualization tools, such as D3.js, Plotly, matplotlib, etc.
- Proficiency in using query languages search as SQL, Hive, Pig
- Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.