Data Scientist

Experience using statistical computer languages (python) to manipulate data and draw insights from large data sets. Experience using a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and knowledge of their real-world advantages/drawbacks. Experience using deep learning architectures (RNN, CNN, LSTM, etc.) and frameworks (Tensor flow, Keras, etc.) Experience in natural language processing Experience using database technologies including SQL, Oracle, SQL Server, or NoSQL databases. Experience using cloud technology and services specifically in AWS including Athena, Glue, Sagemaker, and QuickSight Experience with at least one common OpenSource high-level LLM-framework (e.g. LangChain, Llama-Index), evaluation techniques and agentic principles Familiarity with modern software development, devops strategies and tooling (GitOps) Experience using machine learning models in the automotive industry would be nice to have. A day in the life includes: Working with large data sets and prepping the data for consumption Assessing the effectiveness and accuracy of data sources Working with business users to obtain more insight into data sources. Asking the right questions to understand how the data can be used. Evaluating the results of machine learning algorithms – determining their explainability Determining the feasibility of a use case given the business problem and the available data. Monitoring and analyzing model performance Performing prompt engineering tasks with specific use cases This position requires a minimum of 40% onsite attendance; 2 days each week.