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Facilitate the integration of actual revenue and expense data from the General Ledger, time & Attendance/Payroll systems and eClinicalWorks electronic medical record system with budgeted data to enable transparent various financial analysis to modify organizational behavior as applicable.
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JOB RESPONSIBILITES: Generating proposals and presentations; drafting hardware, firmware, and software flowcharts; writing a bill of materials; modeling and simulating vehicle communication, navigation, and power systems in programs such as MATLAB Developing circuit schematics Completing printed circuit board (PCB) layouts Maturing embedded systems Programming in Python, C, C.
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3-5 years of hands-on experience working with Snowflake, data modeling, ETL processes, and data integration. Expertise in Python, Snowflake, data modeling, and data engineering, along with experience in data visualization tools like Tableau, will be crucial in ensuring the reliability and scalability of MedSpeed’s data infrastructure.
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Engineer : Systems, Software, Safety, Electrical, Mechanical, Aerospace, Aeronautical, Hypersonics, Cybersecurity, Space, Space Systems, Digital, Weapons, Design, Test, Radar, Quality, Sustainment, Controls, Integration, ModSim, MBSE, Satellite, Propulsion, Signatures, Reliability, Launch, Sensing, Data, Structural, Navigation, Modeling, Manufacturing, RF, Aerodynamics, Modeling, Turbine, Acquisition, Instrumentation, Aviation, Flight.
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Focused on data modeling, data quality, data integration and data governance. Strong understanding of relational databases (e.g., Oracle, SQL Server, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra), and data integration technologies (e.g., ETL tools, data virtualization, API integrations.
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Experience monitoring, maintaining, enhancing and managing all system (software/hardware/network/configuration and data management) operations and system administration, integration, and data transfer for modeling and simulation tools, architecture tools, and data repositories within the Naval Integrated Modeling Environment (IME.
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About the Role Responsibilities include but are not limited to:Leading Resource Staffing and modeling in Adaptive Insights including agile model development, data organization, security, data integrity and supporting on-going enhancements for all Resource Management teams.
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Our tech stack spans several languages and frameworks, including but not limited to: Python, Go, Rust, React, running in Docker/Kubernetes on GCP. Relevant areas of expertise might include workflow engineering, tool integration, high performance cloud computing, systems engineering, and machine learning, but specific knowledge of any of these areas is less critical than versatility and a willingness to learn and work anywhere in the tech stack.
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Demonstrated competence in informatics, information integration, data extraction, transformation, & loading (ETL), and/or knowledge modeling. Normalize and represent test results using clinical data standards such as ICD-O-3, FHIR, mCode, LOINC, ICD-10, UMLS, SnoMED, RxNorm, etc.
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WHAT THIS ROLE WILL DO Solution Design: Develop comprehensive data warehouse and platform architecture blueprints, encompassing data modeling, ETL processes, data integration, storage, and data governance.
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Firm understanding of data modeling, master data management, enterprise data warehousing, ETL, reporting, querying, requirements analysis, and data integration techniques.
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The ideal candidate will have expertise with broad range of statistical methodologies suitable for modeling NGS data, characterization of their performance and associated tradeoffs and their integration into computational workflows, including delivery of the key analyses results for the regulatory filings at Verve.
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Study complex data related to donors, listeners, demographics and psychographics, giving, pledging, website usage, streaming media, social media, contacts, and any other available data, using data mining, data modeling, machine learning and predictive analytics and other techniques, seeking out useful, actionable information, both positive and negative, reporting findings to management.
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Master data management (e.g., match/merge, survivorship, data modeling, hierarchy management), data integration (e.g., data conversions/initial loads, high and low latency data movement, event based and schedule based data movement, business process orchestration, data ingress and egress.
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This role requires the expertise of Data Integration, Data Modeling, Business Process Optimization, Master Data Management, Analysis Cubes, and Data Quality Assurance.
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