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We provide self service tools to enable data discovery, data processing, data mining and research, reporting, and machine learning/AI, all built using OCI services and industry standard open source distributed computing tools.
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Strong experience with report development and reporting/analytical tools (SSRS, SSAS, Power BI or Tableau experience a plus), and relational databases (Oracle, Azure database); understanding of database development, data mining and analysis.
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Exposure to data analytics and data mining tools/applications such as Tableau, QlikSense /QlikView, R or SAS. Data Engineers will be deployed to these cities: Austin, TX; Dallas, TX; Bentonville, AR; Charlotte, NC; Cincinnati, OH; Columbus, OH; Hartford, CT; Juno Beach, FL; Mountain View, CA; Basking Ridge, NJ; Mt Laurel, NJ; New York, NY; Oakland, CA; Owing Mills, MD; Pleasanton, TX; Portland, OR; Richmond, VA; St. Louis, MO; Santa Clara, CA; Seattle, WA where you will work alongside other experienced Cognizant associates delivering technology solutions.
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The Company has Bitcoin mining data center operations in central Texas and electrical switchgear engineering and fabrication operations in Denver, Colorado. The HR Generalist will play a key role in supporting our bitcoin mining operations and providing HR services to employees and management.
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M&A is currently seeking a full-time hydrogeologist with groundwater modeling experience to support our mining clients in the western United States. Graduate degree in hydrology, geology, or a related field of study; course work in hydrogeologic data analysis, groundwater modeling, and computer programming preferred.
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Our Impact: The Corporate Data Warehouse (CDW) is a corporate data repository that makes accessible historical and current business relevant data from disparate data sources residing within Freddie Mac's transaction processing and end-user systems into one relational database for decision support, management reporting, ad-hoc and trend analysis, modeling, and data mining purposes.
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We integrate off-the-shelf and new development efforts to sustain and enhance Defense Intelligence Agency’s (DIA) National Media and Exploitation Center (NMEC) architecture by leveraging cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.
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Applies a variety of methods based on standards and metrics to review and improve data acquisition and data management processes such as statistical analysis, machine learning, data mining, predictive analytics, time series analysis, multivariate regression analysis, statistical process control and optimization solutions.
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Job Requirements: PhD degree, or foreign equivalent, in Electrical Engineering, Computer Science, Statistics or Bioengineering or a related field plus 3 years as a Data Scientist or any job title/occupation/position involving Data Sciences.
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The successful candidate will be responsible for contributing to geochemistry water quality and hydrogeology field programs, data analysis, geochemical modeling, technical reporting and other activities for a variety of projects, with a focus on mining.
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We strive to be the premier provider of the safest and most reliable conveyor belting and services to a variety of heavy industrial markets such as coal mining, hard rock mining, sand, gravel, wood handling, power generation, pulp and paper.
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Keep list of data steward up to date in the data governance catalog. Support implementation of data governance capabilities in the data catalog platform. come and join our global team as a Data Governance Intern.
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Mineral Park is an open-pit copper/molybdenum mine located near Kingman, Arizona, a Tier-1 mining jurisdiction. The mine uses conventional open-pit mining methods and processes ore by heap leach followed by SX/EW. Mineral Park is currently in a construction phase to restart milling and concentrating operations.
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Minimum 10 years of relevant working experience in a consulting or regulatory environment, regularly using and analyzing geochemistry data. Possess an in-depth knowledge of Canadian and provincial water quality guidelines, legislation, regulations, guidance, licensing and permitting requirements particularly relating to mining.
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Responsible to analyze the trade / transaction monitoring alert from a trading platform and apply modern data science modeling techniques to predict future disputes & anomalies to proactively manage the risk.
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data mining jobs Title: data Company: Aspca
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