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Keywords: Golang, Web Application, Backend, Gin, Go kit, Java, Spring Boot, MySQL, PostgreSQL, MongoDB, Cassandra, CI/CD, Docker, Kubernetes, Communication, Collaboration, Teamwork, Learning, Growth, Agile (optional), Big Data (optional), Apache Spark (optional), Hadoop (optional), Google Cloud Platform (optional), Cloud Functions (optional), Cloud Run (optional), Cloud SQL (optional), Cloud-Native (optional.
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Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Experience with Cloud Services (AWS, Google Cloud, Microsoft Azure, etc.
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Experience in the Design and implementation of AI/ML models and solutions using Google Cloud Platform technologies, including but not limited to Vertex AI , BigQuery, AI Platform, TensorFlow Extended (TFX), Dataflow, and Compute Engine.
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Possess deep functional and technical understanding of the Machine Learning technologies (Google’s Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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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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Understanding of cloud data engineering and integration concepts. Lead data science projects and partner with cross functional teams to deliver end-to-end advanced analytics/machine learning solution.
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Proven Machine Learning experience and involvement in data science projects and product delivery. Ensure effective designs and quality deliverables in the ML space by designing and developing machine learning and deep learning systems, running machine learning tests and experiments, implementing appropriate ML algorithms.
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Designing and developing machine learning and deep learning solutions and systems. Propose, own initiatives and demonstrate though leadership that improve the efficiency and productivity of the data science Center of Excellence.
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Strong understanding of machine learning principles, including supervised and unsupervised learning, deep learning, and reinforcement learning. Experience with Machine Learning and related technologies such as Python, other relevant libraries and frameworks like PyTorch and tools like Jupiter Notebooks, git.
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The Data Scientist is a key role in the transformation of business. Understanding of exploratory data analysis, descriptive analytics, prescriptive analytics, predictive analytics and so on.
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Cardinal Health Senior Data Scientist in Pierre , South Dakota Fuse is on a mission to disrupt healthcare. Using statistical analysis determine whichdata modelingapproach to use and running / training machine learning tests and experiments.
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This function manages analytic data platforms, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling. Data Science applies base, scientific methodologies from various disciplines, techniques and tools that extracts knowledge and insight from data to solve complex business problems on large data sets, integrating multiple systems.
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Delivery of related information software solutions such as data warehouses and integration platforms. Proactively develops, maintains and evangelizes technical knowledge in Machine Learning and adjacent technologies.
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Approach to use and running / training machine learning tests and experiments. They will work closely with business stakeholders to understand their goals and determine how data science can be used to achieve those goals.
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big data google cloud jobs Title: machine learning engineer
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