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Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Desired Background PhD in Computer Science or related field 4-8 years of professional experience with relevant experience building and designing distributed data systems Knowledge of statistics, data science, AI/machine learning, big data management Strong proficiency in Python and an additional language (e.g., C.
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Demonstrated experience with big data processing systems and distributed computing technology such as Databricks, Spark, Sagemaker, Kafka, Tidal/Airflow, etc. How you will contribute:Be a leader of the RDQ data program that includes integrated data flows with end-to-end data management control mechanisms, internalization of enterprise systems, enablement of automation, near-time data access/streaming data sets, efficient data query review, and flexibly allow inspiring technologies for insight derivation.
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Graduate degree in Management Information Systems, Business Administration and Management, Business Analytics and Information Systems, Statistics, Mathematics, Computer Science, Physics, Economics or a similar degree.
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Currently pursuing a Bachelor’s degree in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field and no experience and will obtain degree prior to first day of employment.
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Oversee the design, development, and management of scalable and reliable data engineering solutions that support data products deployment for use in advanced analytics, data science, and AI initiatives.
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Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline. Stay up-to-date with the latest advancements in data science, machine learning, and related fields, and apply them to improve existing processes and methodologies.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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The Product Director has accountability for creating the vision & strategy, managing the roadmap and executing on the product backlog working closely with cross functional teams across data engineering, data governance, data science and data analytics within AI & Data.
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With the power to apply artificial intelligence and data science to business decisions via enterprise data management solutions, we help leading companies prototype, refine, validate, and scale the most desirable products and delivery models to enterprise scale within weeks.
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YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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Big data Azure AWS Hadoop CIA Confidentiality Integrity Availability SLA Service Level Agreement Jira Confluence Release Manager PIISPII Secret Personal Identifiable Info ITMS Info Tech Mgmt Sys PDLC Java Requirements Traceability Matrix RTM Azure DevOps IT Infrastructure Projects Communicate upgrades maintenance etc to prevent outages.
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Execute the HW Analytics Strategy that includes building a modern Unified Data Warehouse, expanded Self-Service, and Data Science capabilities. 10 years of experience in data engineering, data architecture, BI & Analytics, and/or Data Science.
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FIELD(S) OF STUDY: Data Analytics/Business Intelligence, Computer Science, Business Administration, Industrial Engineering, Mathematics, or related field. A minimum of 2 years of work experience in reporting, analytics, business intelligence, data science or similar field is required.
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Develop and maintain a global strategy for Data Historian (PI) implementation, including Data Model based on ISA95 with Asset and Event Framework, and corresponding Master Data management specific to pharmaceutical manufacturing processes.
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Position Overview: The digital strategy officer will be responsible for setting up, implementing, and managing the overall organization's digital communications strategy to raise awareness about the FNIH brand and its reach and impact in biomedical science and patient outcomes including its leadership, its programs, training initiatives, and events (including fundraising.
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big data science management strategy jobs Title: product manager
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