With the recent addition of Prelert to Elastic, we now have a fully dedicated Machine Learning team in house. Our goal is to further expand our capabilities in developing technologies that allow users to better understand the behavior of their data. Our team has developed an unsupervised machine learning engine that can plow through large amounts of data and automatically find those insights our users today have been proactively finding using search. Current use cases include finding anomalies within transactions / operational metrics, detecting uncharacteristic user behavior, finding a population of attacking IP addresses but we are looking forward to expanding our capabilities to many more in the future. And in order to get there, our team is looking to hire an exceptional Data Scientist to join them. This is an amazing opportunity to join a small, highly experienced team where you can make an immediate impact and contribution to the core of our new machine learning offering.
Your Role:
As a Data Scientist you will contribute to the Machine Learning team within Elastic by performing data analysis on large and complex datasets and represent findings effectively and clearly to various audiences.
To succeed in this role, you will be driven by a genuine interest for understanding and exploring data. You must be able to interpret customer requirements and map these to deliver real business value. Our ideal candidate must strive to seek answers to questions about data that the customer has both asked for, or didn’t yet know they needed.
Typical projects you will be involved in will include:
Extracting valuable insight from real-world datasets. For example,
Understanding customer use cases
Transforming customer data
Analysing customer data using Prelert and/or other statistical tools
Examining Prelert models and results
Summarise dataset and valuable insights extracted from datasets.
Data extract, transform and load activity on large datasets
Generate test data sets for validating analytical functions and methods
Support engineers in development of big data anomaly detection analytic systems
