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Proficient with software used for data mining, statistical analysis, and data visualization (SAS, SQL, R, SPSS, Qlik, Power BI, Tableau, etc.) Understanding and being highly proficient at querying a wide variety of healthcare data and related population data (medical/pharmacy claims, behavioral health claims, health care management (HCM) records, electronic medical records (EMR), provider databases (AMA, NPI, DEA, etc.
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Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices. Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices.
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Assist with testing and data validation activities involving PwC, DSC, RJW, Celigo, and Orderful. Proven ability to manage testing and data validation processes with multiple stakeholders, including PwC, DSC, RJW, Celigo, and Orderful.
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As a VP Data Scientist, you will apply your strong knowledge of ML, NLP, Deep Learning, Knowledge Graphs and experience working with massive amounts of data. Use large scale data processing frameworks such as Spark, AWS EMR for feature engineering and be proficient across various data both structured and un-structured.
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Identify opportunities to leverage technology to improve ability to compile, analyze, and report item creation and data (e.g. smartsheet, access, excel, JDE, Cantor, AQ, etc.) Implement data governance processes for item master data maintenance.
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Data Protection: Develop and implement data encryption, masking, tokenization, and data loss prevention (DLP) solutions to protect sensitive data stored in Azure services. You will lead the design, implementation, and management of security solutions to protect against advanced cyber threats, ensure compliance with regulatory requirements, and maintain the integrity and confidentiality of sensitive data.
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Solid understanding of data center operations fundamentals in networking and power Extensive Linux administration and networking skills are highly required. Experience with: Open source and commercial research related software, Python, R, Matlab, Mathworks, Julia, Ansys, Intel, nVidia cuda and GCC compilers.
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Note: This home based data entry role is designed for earning additional income and should not be viewed as a full-time position. Home Based Data Entry. Note: This home based data entry role is designed for earning additional income and should not be viewed as a full-time position.
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At least 3 years of experience managing Cloud Data Warehouse database technologies, such as AWS Redshift, Snowflake, Databricks or similar. Design, configure, and manage Data Warehouse Database Systems on Cloud (AWS Redshift, EMR HBase and Snowflake.
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The Person: *Experience Python *Experience with geospatial and remote sensing *Experience with SciPy, Pytorch, Tensorflow etc *US citizen The role: *Build Google Cloud Platform data processing pipelines *Apply machine learning, image processing & statistics to problem solving *Develop and test algorithms to demonstrate trade-offs for final selection.
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Design, Implementation, Support Data Center SDN; ACI/NSX, Arista CloudVision. The role of the Data Network Implementation Engineer is to provide technical implementation services to support the evolution and ongoing support of the IP Network in response to projects (all types), upgrades, service, and feature enhancements and for remediation/break-fix services.
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If you have had experience in any of these job titles, Construction Project Engineer, Construction Data Specialist, Construction Document Specialist, Construction Support Data Specialist, you might be a good fit for this position.
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Experience with Extract/Transform/Load (ETL) or Extract/Load/Transform (ELT) tools, including both batch and real-time data transmission applications such as SSIS, Informatica, Kafka, Spark, MuleSoft, or equivalent software.
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For internal candidates) - Working knowledge of internal data platforms (ICDW, Cloud sources) and/or applications (Customer Assist, First Assist, IDMS, Quest, Join our team as a Vice President, Quant Analytics Manager - this is your moment to make a difference and advance the strategic direction of technology for JPMorgan Chase As a Quant Analytics Manager within the Consumer and Community Banking Operations Analytics Data Assets Team, you will play a pivotal role in the engineering, development, and deployment of analytic datasets and solutions.
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Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka. Expertise in architecting, designing, and building end to end data platforms in the GCP environment using BigQuery and other services while adhering to best practices guidelines such as open standards, cost, performance, time to market and minimize vendor lock.
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data job Title: data architect Company: Spectrum in Richardson, TX
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