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Experience with Python/R, SQL, UKG, Snowflake, Salesforce, NetSuite. Position Summary: The Senior Manager of Data Analytics predominately uses a tech stack of Power BI, SQL, Visual Studio Code, Snowflake, and Excel to answer questions to data that is ETL’d from our ERP, CRM, and various internal and external data sources.
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Some of the high priority skills include: quantitative research; experience modeling for predictive analytics and program evaluation; experience with R and/or Python, and natural language processing; process/clickstream data analysis; and machine learning (e.g. unsupervised learning, predictive analysis, automated feature extraction.
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Minimum 5 years of experience utilizing various tools such as Python, R, SQL, or Tableau, and reporting platforms with the ability to represent data through reports, dashboards, scorecards, or KPIs. In lieu of 5 years of analytics tools experience, a Master's Degree in a relevant program plus 2 years of experience will be considered.
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Requires proficiency in SAS, R, or Python (preferred) for data wrangling, automation, and creating statistical and machine learning models. The Business Data Analyst, Senior will report to the Sr. Manager of Back Office Analytics.
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The courses may include Foundations of Data Analytics and Programming, Advanced Excel for Data Analytics, Data Governance, Management and Quality, Data Visualization-Power BI, Data Visualization-Tableau, Data Privacy and Integrity, Data Protection, Descriptive Analytics, Predictive Analytics, Data Complexity, Cloud Analytics, Big Data, various programming courses and concepts involving python, r and ML, and database courses (including MySQL, Microsoft SQL Server and NoSQL alternatives.
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Experience in machine learning methods (e.g. multivariate regression, feature engineering, random forests, XGBoost, elastic nets, hierarchical bayesian regression, unsupervised learning, clustering/segmentation)Key Skills: Data Science, AI/ML, SQL, R, Python, C.
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Set the foundation for AI-first features by architecting the data infrastructure in a way that enables advanced analytics, machine learning, and predictive modeling. Experience implementing automated reporting and dashboarding solutions using BI tools (e.g., Tableau, Thoughtspot) and scripting languages (e.g., Python, R) to extract insights from data.
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Strong technical skills: Programming tools (i.e., R, Python); Cloud Software (Azure ML, Google Analytics, Snowflake); data visualization tools (i.e., Tableau, Qlik Sense); data querying tools (i.e., SQL.
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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 agency looks to the Analytics group for direction, strategic thinking, and prowess in data science. Familiarity with programming languages is a plus (R, Python, dbt, SQL.
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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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data science predictive analytics python r jobs Company: Cvs Pharmacy
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