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Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
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Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.
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Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems, backend, large-scale systems, data science, full-stack.
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6 years An equivalent of 6 years experience with big data, database query and analysis languages (e.g. Python, SQL, Snowflake SQL, R, Scala, SAS, Azure DataBricks) and data visualization tools (e.g. Power BI, Tableau) required.
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Stay ahead of emerging technologies and methodologies in data engineering and machine learning. Metropolis is seeking a Senior Machine Learning Data Engineer to play a crucial role in architecting, implementing, and managing our ML data ecosystem to support advanced machine learning initiatives.
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You will develop robust and scalable data pipelines, ML model hosting, and backend services for enterprise line of business applications in Python, VertexAI, Airflow, dbt, Flask, PostgreSQL, BigQuery, Docker, Kubernetes, and more.
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Expertise in the physics of additive manufacturing processes such as wire arc DED and laser powder DEDExpertise in physics-based simulation and its integration with machine learning models.
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Data Scientists contribute to projects involving one or more of the following disciplines: Data Science, Applied or Theoretical Machine Learning, Deep Learning, Deep Reinforcement Learning, Physics Inspired ML, Classification Systems, Natural Language Processing, Artificial Intelligence, or Computer Vision.
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They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments.
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The Data Analyst is responsible for overall DTC systems master data quality and will work with appropriate partners to ensure proper controls and audits are in place to avoid data driven issues.
$63,000 - $80,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Demonstrated experience with data mining, machine learning, data science and data interpretation techniques. Research, Teaching, and Learning (RTL) at UC Berkeley is looking for an experienced data engineer with a data science background to be part of a new initiative supporting Learning Analytics.
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This position will be responsible for overseeing the design, development, and implementation of business intelligence solutions, with a strong focus on Microsoft Power BI, data warehouse management, ETL processes, and statistical data analysis.
$115,000 - $130,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Proficiency in programming languages such as R, Python, and SQL, with experience in data analysis and machine learning tools like PyTorch, Pandas, scikit-learn, Tensorflow, or similar.
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The role oversees and manages the Development QA team and interacts cross-functionally with functional teams who interact with and/or support Preclinical and Clinical Trials, which include Preclinical and Clinical Operations; and, Product Development, GMP teams, Pharmacovigilance, Medical Writing, Biostatistics and Data Management to ensures compliance to the Quality Management System (QMS) and all applicable regulatory requirements.
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Proficiency in Yardi, Nexus and/or other ERP software systems is a plusProficiency in advanced data analytics tools such as PowerBi or Tableau is a plusUnderstanding of basic concepts in data base management such as Azure, SQL, et cetera is a plusBeing able to quickly master new software packages is a must.
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