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Experience working with large-scale data mining and reporting tools (examples: SQL, MS Access, Essbase, Cognos) and other financial systems (examples: Oracle, SAP, Lawson, JD Edwards) This team encompasses cost management associated with Under-the-Roof (UTR) operations across NACF, Amazon Logistics (AMZL), Amazon Extra Large (AMXL), North America Sort Center (NASC), and Rapid and Rural Logistics (R2L.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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Data Scientist II, Department of NeurologyClinical Informatics and Natural Language Processing / Machine LearningWhy UT Southwestern Medical Center? A multi-year Data Scientist position is available in the Department of Neurology and the Clinical Informatics Center at UT Southwestern Medical Center.
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6 years of experience must include: Ab initio, Informatica, Data Stage; Teradata, IBM DB2, Cognos, Oracle PL SQL; Autosys, Control-M, Erwin, XML, HTML, CSS, Unix Shell Scripts; Data Analysis, Data Processing, Code Optimization, Performance tuning; Automating Business Process and Models; Microsoft Visio, Web Services, Crystal Reports; and HP Quality Center, ALM, VSS, EME, XSD. At least 3 years must include: Hadoop, HDFS, Big Data, Hive, Spark.
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6+ years of experience in SQL, data transformations, statistical analysis, and troubleshooting across more than one Database Platform (Cassandra, MySQL, Snowflake, PostgreSQL, Redshift, Azure SQL Data Warehouse, Databricks, etc.
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Technical Acumen: Perform model training and validation using various types of machine learning techniques on structured/unstructured data, including imagery, text and graphs. Technical Oversight: Provide technical guidance on model training and validation using various machine learning techniques on structured/unstructured data, including imagery, text, and graphs.
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Leverage Azure Databricks for big data processing, machine learning, and analytics workloads. 5-6 years of hands-on experience with Azure services, specifically Azure Databricks, Azure DevOps (ADO), Azure Data Factory, Azure Data Lake Storage Gen2 (ADLS Gen2), and SQL Server.
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Support vendor risk management and DPIA programs to ensure third parties comply with the Firm’s privacy and data protection requirements. This role requires Data Loss Prevention (DLP) program experience, including conducting investigations related to data loss, data exfiltration, or unauthorized access or use of data, or experience using eDiscovery solutions or similar technology.
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Reports to: VP Data Science. The AVP will also lead and guide the data science team with modeling expertise in forecasting, optimization, data mining, analysis and analyzing complex datasets; lead and guide in the use of descriptive and supervised machine learning methods and advanced statistical methods using innovative and the latest advanced technique and algorithms; and lead and guide in the production of research and analysis to quantify the impact of internal and external environments on portfolio performance.
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2+ years of experience in cloud ETL tools (Azure data factory, AWS glue) withExperience working with data warehouse tools (Snowflake, Databricks, Redshift etc.) Validate data sources, extraction, transformation logic and upload of data into target tables ( ETL pipelines)Design, develop, and implement comprehensive data quality tests to identify anomalies, inconsistencies, and data integrity issues for new product development initiatives, product changes, policy changes, and database changesWork with other engineers and support teams to identify, log, root-cause, triage, prioritize, and drive resolution of defects.
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We are seeking candidates experienced in Digital Transformation, particularly those proficient in Data (SME), and skilled in forming Strategic Partnerships with data platform companies like Snowflake and Databricks.
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Job Responsibilities: Team Leadership and Development:Lead, mentor, and develop a team of data scientists and machine learning engineers. Demonstrated experience leading and mentoring junior data scientists.
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Position Responsibilities:Classify aerospace parts, components, tooling, assemblies, and kits under the US Harmonized Tariff Schedule (HTS), Sch B, ECCN, and USML.Lead the classification process (maintaining current master data, Part build process, Chemical Weapons Convention Global controls, Montreal Protocol, Mercury, Biobar, TSCA, FDA, Drug Precursors, Civil Duty Relief Programs, Drawback.
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Data entry clerks come from all different backgrounds including, data entry, telemarketing, customer service, sales, clerical, secretary, administrative assistant, warehouse, inventory, receptionist, call center, part-time, retail fields & more.
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Experience working with Big Data technologies: Spark, Databricks or other frameworks. The candidate should possess intellectual acumen, with an engineering mindset and an interest in developing enterprise scale solutions using industry recognized cloud platforms, databases, data integration/orchestration tools, and big data technologies.
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Title: big data Company: Amazon in Dallas, TX
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