Data Engineer

Summary

B/CORE is committed to delivering impactful solutions for government missions. They are seeking a Data Automation Engineer to conduct sophisticated analysis, clean and organize data, and implement advanced ETL processes to support customer missions.

Responsibilities

• Conduct sophisticated analysis using deployed tools and natural language processing
• Analyze large amounts of raw data, including text data, to provide business insights
• Clean structured and unstructured Sponsor data, including text data
• Design and implement advanced ETL code and table configurations for complex data sets
• Use Structured Query Language (SQL) in Sponsor’s Oracle database to develop and organize relevant information with supporting analytics
• Independently, or with a team, author analytic publications and produce ad-hoc reports to include data visualizations using the Sponsor’s templates
• Implement the Sponsor’s existing coordination process
• Provide technical education to staff on an ad-hoc basis
• Provide subject matter expertise in NLP to support Sponsor’s initiatives

Skills

• Demonstrated professional or academic experience performing NLP tasks, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance
• Demonstrated professional or academic experience using Python NLP packages such as Spacy, Gensim, or NLTK to analyze or process collections of documents
• Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras
• Demonstrated professional or academic experience with the HuggingFace Transformers library and hub
• Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (Scikit-learn) or deep learning models
• Demonstrated academic or professional experience using encoder-decoder and generative language models to perform NLP tasks
• Demonstrated academic or professional experience communicating methodological choices and model results
• Demonstrated professional or academic experience and proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries
• Demonstrated professional or academic experience with version control systems such as Github and Jenkins
• Demonstrated experience leveraging GPUs for accelerated computing
• Demonstrated experience writing Python scripts that pull data from web-based APIs and relational databases
• Demonstrated experience with cloud computing development and architecture
• Demonstrated experience with front-end web development frameworks such as Flask
• Demonstrated experience developing applications for semantic search
• Demonstrated experience tuning LLMs on custom data sets and applying results to specific use cases
• Demonstrated professional or academic experience and proficiency with Tableau to produce visualizations and dashboards

Qualifications

Must Haves

• Demonstrated professional or academic experience performing NLP tasks, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance
• Demonstrated professional or academic experience using Python NLP packages such as Spacy, Gensim, or NLTK to analyze or process collections of documents
• Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras
• Demonstrated professional or academic experience with the HuggingFace Transformers library and hub
• Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (Scikit-learn) or deep learning models
• Demonstrated academic or professional experience using encoder-decoder and generative language models to perform NLP tasks
• Demonstrated academic or professional experience communicating methodological choices and model results
• Demonstrated professional or academic experience and proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries
• Demonstrated professional or academic experience with version control systems such as Github and Jenkins
• Demonstrated experience leveraging GPUs for accelerated computing

Nice to Haves

• Demonstrated experience writing Python scripts that pull data from web-based APIs and relational databases
• Demonstrated experience with cloud computing development and architecture
• Demonstrated experience with front-end web development frameworks such as Flask
• Demonstrated experience developing applications for semantic search
• Demonstrated experience tuning LLMs on custom data sets and applying results to specific use cases
• Demonstrated professional or academic experience and proficiency with Tableau to produce visualizations and dashboards