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Use advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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This analyst will have detailed knowledge and understanding of business intelligence functions including but not limited to analytics, data mining, data warehouse, reporting and visualization dashboards.
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Experience supporting a data science and machine learning organization end-to-end Experience creating a strong team environment across a large set of separate agile teams and stakeholders Experience in change management and digital transformation Leadership and team management skills.
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Use Excel, SQL, and data visualization tools such as Power BI to analyze and aggregate data generated by Self-Help's programmatic activities. Work with DPI colleagues in fundraising, investor relations, compliance, policy, impact assessment, and community engagement to ensure that data systems, analyses, and reports are adequately serving their needs and work with Self-Help's Data Intelligence Group (DIG) to optimize them.
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Collaborate with team members on shared code/analysis scripts using Git/GitHub. Conduct research related to specific topics in watershed and receiving water modeling and analysis, remote sensing and machine learning, and water quality management studies.
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Understands, conducts, and documents appropriately Dialysis/Apheresis machine safety tests/alarm tests, equipment calibration, dialysate testing, machine safety tests, functional testing, and internal and external disinfection on all water & dialysis machines, and complies with the documentation/notification standards per FMS policies.
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The Assistant Vice President for Data Strategy and Governance (AVP-DSG) will serve as the leader for developing and implementing strategies associated with research data governance, security, and compliance at Duke University.
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Onyx Product Management is at the heart of our mission, ensuring that everything from our infrastructure, to platforms, to end-user-facing data assets and environments is designed to maximize our impact on R&D. The Product Management team partners with R&D stakeholders and Onyx leadership to develop a strategic roadmap for all customer-facing aspects of Onyx, including data assets, ontology, Knowledge Graph / semantic search, data/computing/analysis platforms, and multi-omics applications.
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The Scientific Knowledge Engineering team, which sits within the Onyx Product Management organization, is responsible for the data modeling, ontology definition and management, vocabulary mapping, and other key metadata activities that ensure Onyx platforms and data assets speak scientific language.
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Maintains, repairs, and occasionally operates construction or power equipment, including but not limited to an excavator, grader, bulldozer, backhoe, front end loader, skid steer, asphalt paver, dirt/asphalt roller, asphalt reclaimer, soil stabilizer, and asphalt milling machine.
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Experience with financial data sources like FactSet, Bloomberg, and others (Plus). Experience in building and designing solutions for data warehouse and experience in working with large data sets in Oracle and Snowflake.
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Some working knowledge of relational databases, SQL, and/or Python or a comparable scripting language to perform machine learning tasks (such as text analysis) or automated processes (such as web-scraping.
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Experience with preferred cloud data technologies such as Oracle, Snowflake, PostgreSQL, GoldenGate, PowerBI/Tableau. You will be responsible for developing data architecture, data blueprints, hands on data modeling, design, data movement, master data management, analytics and enabling data science.
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This role is responsible for maximizing the value of our data assets over a lifetime to bring purpose to data by acting as translators of highly technical information from domain experts into an appropriate data model - complete with significant ontology and vocabulary that can be utilized to effectively structure and index the data.
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In depth knowledge in a variety of analytics techniques including: profiling, data mining, modeling, statistical analysis, campaign measurement and reporting. Experience working with data environments and strong knowledge in querying language and/or querying applications (SQL, Alteryx, BRIO.
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machine learning data mining jobs in Durham, NC
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