Vacancy caducado!
- Conduct theoretical research in collaboration with academic partners.
- Develop SQL queries to extract and wrangle data.
- Apply advanced statistical and predictive modeling methods including various time-series-based deep learning models such as Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU).
- Identify data requirements, available data sources, and expected outcomes.
- Recommend and support data collection, integration, and retention requirements by assessing the effectiveness and accuracy of data source and data gathering techniques.
- Develop experimental design approaches to validate findings or test hypotheses.
- Identify opportunities and find solutions hidden in large data sets to improve features and applications.
- Provide ongoing performance tracking and monitoring of statistical models and recommend ongoing improvements to methods and algorithms.
- Demonstrated experience solving loosely defined problems by leveraging pattern detection over potentially large data sets.
- 2+ years of statistical modeling using tools such as Python, MATLAB, R, and/or SAS.
- Experience creating and using advanced machine learning and deep learning algorithms and statistics.
- Experience applying statistical techniques and concepts.
- M.S. or Ph.D. with focus on Data Science, Computer Science, Statistics, Machine Learning, or a similar area of study.
- 2+ years of industry experience with data storage and analysis tools such as SQL or other big data frameworks.
- Experience with Intelligent Transportation Systems (ITS) or vehicular data.
- Familiarity with either telematics, wireless networking, or V2V V2I communications protocols.
- Experience programming within Unix-based operating systems, such as Linux.
- Programming in Python.
- Ph.D. with a focus on Data Science, Computer Science, Statistics.
Vacancy caducado!