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The Sponsor provides training, tradecraft guidance and tools for the data science workforce that improve the reuse of successful data science methods. The Sponsor’s office completes short-term prioritized data science projects, which require programmatic and technical support. The work is performed within a team environment and requires constant iteration with stakeholders to provide services and tools. Work will include development and maintenance of training, publication and coordination of tradecraft guidelines and services as well as development of programming packages and data services to support cross-enterprise needs. Work will include high technical skill in programming as well as high levels of collaboration, communication and requirements solicitation.
Job Responsibility:
Development and maintenance of training, publication and coordination of tradecraft guidelines and services
Development of programming packages and data services to support cross-enterprise needs
Completion of short-term prioritized data science projects, which require programmatic and technical support
Work within a team environment and requires constant iteration with stakeholders to provide services and tools
Requirements:
Demonstrated experience with data engineering, to include designing and building data infrastructure, developing data pipelines, transforming/preparing data, ensuring data quality and security, and monitoring/optimizing systems
Demonstrated experience with data management and integration, including designing and operating robust data layers for application development across local and cloud or web data sources
Demonstrated work experience programming with Python
Demonstrated experience building scalable ETL and ELT workflows for reporting and analytics
Demonstrated experience with general Linux computing and advanced bash scripting
Demonstrated experience with SQL
Demonstrated experience constructing complex multi- data source queries with database technologies such as PostgreSQL, MySQL, Neo4J or RDS
Demonstrated experience processing data sources containing structured or unstructured data
Demonstrated experience developing data pipelines with NiFi to bring data into a central environment
Demonstrated experience delivering results to stakeholders through written documentation and oral briefings
Demonstrated experience using code repositories such as Git
Demonstrated experience using Elastic and Kibana technologies
Demonstrated experience working with multiple stakeholders
Demonstrated experience documenting such artifacts as code, Python packages and methodologies
Demonstrated experience using Jupyter Notebooks
Demonstrated experience with machine learning techniques including natural language processing
Demonstrated experience explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats
Demonstrated experience developing tested, reusable and reproducible work
Work or educational background in one or more of the following areas: mathematics, statistics, hard sciences (e.g. Physics, Computational Biology, Astronomy, Neuroscience, etc.) computer science, data science, or business analytics
Nice to have:
Demonstrated experience with cloud services, such as AWS, as well as cloud data technologies and architecture
Demonstrated experience using big data processing tools such as Apache Spark or Trino
Demonstrated experience with machine learning algorithms
Demonstrated experience with using container frameworks such as Docker or Kubernetes
Demonstrated experience with using data visualization tools such as Tableau, Kibana or Apache Superset
Demonstrated experience creating learning objectives and creating teaching curriculum in technical or scientific fields