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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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The successful candidate has a scientific background in operations research, engineering or other STEM field and has expertise in one or more of the following areas: data science, data analytics, data engineering, data visualization, supply chain planning, statistics, machine learning, predictive modeling, decision analysis under uncertainty, artificial intelligence, Python and/or R, app development, and Tableau dashboard development.
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Utilizing Data analytics skills and experience developing mathematical models in R, Python, SAS, MATLAB, and/or SPSS; Working with analytics and construction management software packages including Cora, Power BI, Primavera P6, Primavera Unifier, [redacted], Tableau.
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Construction Management, Materials Science, Materials Science and Engineering, Project Engineering & Management, Risk Management, Civil Engineering, Mechanical Engineering, Electrical Engineering, Industrial Engineering.
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Preparing and modeling data in SQL, Tableau, and/or Qlik; Data center construction and engineering. Demonstrating experience with data cleansing, conversion and migration; Managing and directing on-shore and off-shore resources to organize and profile large data sets to develop risk models.
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Use data and insights to inform conclusions and support decision-making. Participating in the assessment and improvement of business processes, including leveraging Cora, Primavera Unifier or other project technologies; and.
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Professional Engineer (PE), Project Management Professional (PMP), or American Production and Inventory Control Society (APICS). Power generation including renewable energy assets; We advise and support clients as the plan, deliver, and optimize capital projects and programs.
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KEY QUALIFICATIONS: Python, SQL Data processing, ML experience Data Warehouse knowledge ETL pipeline knowledge Data Engineering Data Science Data Analytics, Data Mining PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: Kubernetes, Tableau, PowerBi MongoDB Microsoft Cloud Services like Azure and AKS Snowflake SQL Server data platform Software development (including design, implementation, testing, and change management.
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Strong knowledge of Python (Pandas DataFrames and accessing APIs), Azure (DevOps and Function Apps), PostgreSQL, QGIS and/or ESRI ArcGIS to perform data analysis and visualization. Utilize tools such as Python (Pandas DataFrames and accessing APIs), Azure (DevOps and Function Apps), PostgreSQL, QGIS and/or ESRI ArcGIS to perform data analysis and visualization.
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Extracts data using a variety of a programming languages, such as SQL, SAS, Python, or Spark/Scala, and applies knowledge of relational and non-relational database systems housed on both on-premise and off-premise (hybrid) platforms.
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The ideal applicant should have a strong programming background (e.g., Python, R, SQL, SAS, and/or STATA) and the drive and enthusiasm to learn about clinical care by assisting in state-of-the-art patient-centered research.
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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. Strong proficiency in Python, R, SQL, and experience with libraries/frameworks such as PyTorch, TensorFlow, and Scikit-learn.
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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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Manipulates and extracts Medicare, Medicaid, and other healthcare claims data stored in Cloud environment using appropriate software such as SAS, Snowflake, Python, R, SQL, and other software as appropriate for the task.
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Background with data visualization tools such as Power BI, Tableau, Datorama, Domo. Experience working with Clickstream web analytics tools such as Adobe Analytics, Google Analytics, Mixpanel, HEAP or Amplitude.
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data science predictive analytics analyst python r jobs Company: Cvs Pharmacy
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