• Own and operate machine learning models that run in production, including monitoring, debugging, and iterative improvement. • Develop, train, and optimize models used in a real-time or near-real-time bidding and decisioning system. • Work with stakeholders to clarify ambiguous problems, define success metrics, and translate business needs into technical solutions. • Design and implement feature engineering pipelines, balancing model performance, latency, and maintainability. • Write production-quality Python code (not just notebooks) and collaborate with engineering on deployment, CI/CD, and system design. • Analyze model behavior using logs, metrics, and offline analysis to identify performance issues and opportunities. • Contribute to data pipelines and infrastructure where needed (e.g., ETL, materialized tables, model inputs). • Make thoughtful tradeoffs between something that is “theoretically optimal” and something that is reliable, fast, and shippable.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Jupiter seeks a highly skilled Flood Modeler (contract), with a specialized focus on development and execution of shallow water flood models to support our high-resolution flood modeling pipelines. The purpose of this role is to develop and deploy complex modeling frameworks to simulate and predict flood risk on commercial cloud platforms. This role will involve: - Deploying algorithms for numerical simulation/prediction of flood risk resulting from rainfall, river flow, and coastal storm surge. - Troubleshooting complex algorithms. - Applying code iteratively to test new settings. - Contributing to process workflows. - Assuring quality of output. This role is a critical piece of the team delivering data that forms the backbone of Jupiter products. Qualifications - Master’s degree in Civil/Environmental Engineering, Coastal Engineering, Water Resources, Fluid Mechanics, Hydrology or related field. - Bachelor's degree plus 3-5 years experience also considered. Requirements - 2-dimensional flood model design and deployment (e.g. HEC-RAS, LISFLOOD, TUFLOW, Telemac, or similar). - Model parameter optimization. - Model validation and verification. - Geospatial data processing (QGIS, ArcGIS). - Strong knowledge of Python and experience with libraries such as NumPy, GDAL, Rasterio, Xarray, and Pandas. - Familiarity with software engineering best practices and cloud computing. - Fortran experience a plus. - Experience modeling channel, coastal and floodplain inundation hydrodynamics. - Experience scaling computational methods for large-scale processing (Docker containers, Kubernetes, AWS EC2, Dask, multiprocessing). Benefits - $50 - $55 an hour.

• Align with business, clinical, and technology stakeholders on analytics strategies • Assist the EM/AP to develop contracts, statement of work (SOW), targeted proposals • Manage the intake of such initiatives & client requests and assist the EM/AP to develop proposals • Provide information and data analytics for and report to the EM or research leader • Work with Senior Vice President (SVP), Business Development to assist with sales calls • Prepare and coordinate the necessary materials for each client meeting • Develop, coordinate, and organize business and meeting schedules for BD team members

• Designing and enhancing risk-based analytic models to identify high-risk providers, services, and utilization pattern • Conducting exploratory and targeted data analyses to support CMS program integrity initiatives • Supporting development of dashboards, visualizations, and reporting products for CMS leadership and technical staff • Collaborating with the prime contractor and CMS to refine analytic methodologies, assumptions, and outputs • Translating analytic results into clear findings, documentation, and recommendations usable by non-technical audiences