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Prior experience with Radiology Information Systems, PACS, Data processing and digital data transfer process. Registered X-Ray Technologist by American Registry of Radiologic Technologists (ARRT.
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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area; PhD degree preferred.
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Leading the design, build, migration, and testing of OneStream for multi-dimensional data models (dimensions, hierarchies, attributes); input template and report build; Data Integration and Extract Transform and Load (ETL) concepts; understanding of calcs (allocation, top-down spreading, currencies); and, workflow, data permissions and security.
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Develop and optimize big data processing using Spark and PySpark within the Databricks environment. Design and implement scalable and secure integration solutions between the data sources and our data pipeline infrastructure.
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Collaborate with different teams in EDM (Data Cloud, Architecture, Data Governance Tech, Data Science) and support strategic initiatives such as data governance, data-as-a-service, and self-service analytics.
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Experience designing eDiscovery databases and reports; reviewing and quality checking database data loads; coordinating complex projects; developing recommendations, plans, cost estimates, budgets, procedures, and specifications for case-specific projects from discovery to trial phase; drafting project proposals and provide status reports; providing end user support and customer service; troubleshooting litigation support firm applications; processing experience a plus.
$111,200 - $166,800 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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8+ years of experience in data engineering or full-stack quantitative analytics/data science roles. Experience automating data integration using APIs. Experience working with data SaaS and BI tooling (Fivetran, Looker, Databricks, etc.
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ARM will serve as the key contact and lead for access and reimbursement support-related matters and is responsible for being the local market access expert on payer policy coverage, multi-channel acquisition pathways, billing and coding, claims processing, reimbursement, and integration of manufacturer support programs into a range of account workflows.
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BA/BS degree in Data Science, Statistics, Computer Science, Engineering, Public Health Information, Bioinformatics, or equivalent quantitative field. The Senior Strategic Data Scientist at CoverMyMeds makes a significant contribution to the success of our company.
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Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements. Strong experience with Databricks and Apache Spark for data processing and analytics.
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Utilize Databricks for data processing. The role demands comprehensive knowledge of ETL and end-to-end data testing to support backend transformation and data integration projects.
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The SAP MM (SAP Materials Management) analyst will support the ongoing SAP ECC implementations and other systems specific to the areas of Procure to Pay (also known as PTP, MM or Materials Management), Master Data, Contract Management, Pricing, Rebates, Purchase Order processing, warehouse inbound process and Transportation/Logistics related functions and capabilities.
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Program cognitive tasks, software pipelines, data visualization tools, and machine learning or data science utilities for a variety of scientific use cases. The Scientific Software Engineering Generalist responsibilities include writing, debugging, and testing code for arbitrary signal processing and data analysis tasks, software packaging, and the development of training resources.
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Your role as a Data Engineer: In this role you will be responsible for designing, developing, and maintaining data pipelines in support of data management functions such as data engineering, data integration and data quality and governance activities.
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ML Ops: Design and Build customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domainsTechnical Expertise: Serve as the subject matter expert on AI technologies, including machine learning, natural language processing, computer vision, and other relevant domains.
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data science processing integration jobs Title: engineer in Kearny, NJ
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