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Technical Skills: Proficiency in SQL, database platforms (e.g., MySQL, Oracle, SQL Server), data warehousing, ETL processes, data modeling tools, and familiarity with cloud services (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and data pipeline tools (Apache Kafka, NiFi.
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Proven expertise in AI Services, Cloud Services, Cybersecurity, IT Operations, Program Management, Network Engineering and Administration, Disaster Recovery, Data Center Operations, Cloud Engineering, Data Architecture, and Data Engineering domains.
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Applications include, but are not limited to, transcriptomics, pharmacogenomics, in vitro/in vivo safety data, histopathology image analysis, and molecular data integration. The Senior Data Scientist will work with diverse biology-related datasets, ranging from pharmacology, toxicology, pathology, genomics, and chemistry, applying data science and machine learning techniques.
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Proficiency in data visualization tools (, Tableau, Salesforce CRMA), SQL and SAQL, and statistical analysis software (, R, Python). The ideal candidate will have strong analytical skills, extensive experience with data visualization tools such as Salesforce CRMA and Tableau, and a deep understanding of fundraising metrics and processes.
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Experience building and managing production-grade data pipelines using tools such as Airflow, dbt, DataHub, MLFlowExperience building and managing production-grade data platforms using distributed systems such as Kafka, Spark, Flink and/or others.
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Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS) and modern data warehouse tools (Snowflake, Databricks) Collaborates with Enterprise Data Strategy team peers including Governance Lead, Lead Data Scientist and Enterprise Data Platforms as well as Information Services Peers including but not limited to IS Strategic Partners, Information Security and the Enterprise Architect.
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Minimum of 5 years of experience in data engineering, specifically with extensive use of Power BI and DataBricks. The successful candidate will be responsible for managing the Power BI platform, advancing data modeling in DataBricks, and leading a team of data engineers and visualization developers.
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Experience with cloud and modern data science tools and platforms such as Databricks MLFlow, GCP BigQuery, AWS SageMaker, Kubeflow, and Azure ML. Experience using data visualization tools such as Tableau, Qlik, or Power BI.
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Expertise in cloud technologies preferably AWS. Expert experience with Data Engineering tools such as Talend, SAP BODS, Kafka, Python, PySpark, Python APIs, Kubernetes, S3, Glue, Athena, EMR, etc.
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Improve data governance: Work closely with Data Engineering, IT and Systems teams to enhance data governance and improve the quality and capabilities of our people analytics data.
$174,000 a yearFull-timeExpandApply NowActive JobUpdated 16 days ago - UpvoteDownvoteShare Job
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Experience in Data Engineering leveraging AWS Redshift, S3, Glue, Airflow, Python, SQL and Kubernetes. Implement data pipelines using tools such as Apache Airflow, AWS Glue, Redshift, S3, Python, and Informatica Cloud.
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The Conservation Data Scientist will work with the University of Texas Insect Collection Curator and the Texas Department of Parks and Wildlife to aggregate, filter, and analyze publicly available biodiversity data on Texas invertebrate species, with the goal of presenting a set of estimated conservation status metrics and related tools on a public website.
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10+ years of designing solutions utilizing key data providers and hyperscalers (e.g., Snowflake, Databricks, AWS Sagemaker/Bedrock, GCP AI Platform/Vertex AI, and Azure). 10+ years hands-on experience working with large scale data solutions; covering strategy, data preparation, data quality, ETL, data visualization.
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Demonstrated proficiency with data science languages (R, Python, SQL, Julia, SAS) and visualization tools (Tableau, Spotfire, SAS, JMP, RShiny) The Clinical Data Analyst partners cross functionally to identify risk to data integrity throughout the data flow to drive quality collection for non-EDC data sources (fluid & tissue labs, digital, imaging, wearables) in Dyne's clinical studies.
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Prefer that the candidate have one of the following certifications: AZ-305 – Microsoft Azure Architect Design DP-100 – Designing and Implementing a Data Science Solution on Azure DP-203 – Microsoft Certified: Azure Data Engineer Associate DP-500 – Azure Enterprise Data Analyst Associate Additional information: Benefits Included: Medical, dental, and vision coverage designed to help you and your family live a healthy lifestyle.
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data job Company: Rlj Dental in Sanford, Florida
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