GovCIO - Atlanta, GA
posted about 2 months ago
GovCIO is currently seeking a Technical Data Scientist/ETL Engineer to join our ETL Team, which is dedicated to ingesting and visualizing data from various cloud sources while alerting on deviations from normalization. This position is fully remote, allowing for flexibility while working from anywhere. The successful candidate will be responsible for developing, inspecting, mining, transforming, and analyzing data to create descriptive and predictive models that significantly impact productivity and decision-making processes, ultimately providing strategic mission impact. In this role, the engineer will apply data wrangling tools, including ETL and ELT processes, along with programming languages to collect and blend data from both operational and relevant external systems. The position requires a strong focus on data analysis, utilizing data mining, machine learning, and statistical analysis to create predictive and descriptive models. The engineer will also be responsible for applying and integrating these models to develop various analytical techniques such as segmentation, clustering, forecasting, and classification. Data visualization is a key component of this role, as the engineer will use data discovery and visualization tools to interpret and present findings in a compelling and usable manner. Maintaining and integrating analytical systems with operational systems is crucial, as is verifying the accuracy of the data and analytics produced. The engineer will interact with both business and data subject matter experts (SMEs) to ensure that the insights generated align with business needs and priorities. The role also involves generating new business insights through the extraction, storage, transformation, analysis, and visualization of diverse data sets. The engineer will collect and transform structured, unstructured, relational, and NoSQL data using ETL and ELT tools, as well as develop custom code using various programming languages. Understanding and utilizing distributed methods, such as MapReduce, to scale to multi-Terabyte data collections is essential. The engineer will analyze data using data mining, machine learning, and statistical algorithms available in commercial off-the-shelf (COTS) tools, building analytical solutions using programming languages and libraries. The position requires interpreting and evaluating the accuracy of results through iterative, agile methods, and applying data discovery and visualization tools to develop actionable data stories.