We are looking for a Data Scientist who will substantially contribute in the product development of a drone health management system, primarily defining hypotheses on available data, implementing experiments with various techniques based on those hypotheses and validating them over time.
The ideal candidate has strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a very good foundation in software development and are able to implement their data driven work into technical solutions as part of the software team. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Work with operation and engineering to identify relevant data for the health management system and how it affects the aircrafts.
Mine and analyze data from the fleet data storage.
Develop custom data models and algorithms to apply to data sets.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Analyse failures and data leading up to failures to define predictive models.
Strong problem solving skills with an emphasis on product development.
Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques.
Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field.
Full time, can be remote
US time zone ideal