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Coding in SAS & SQL Skills. Advise experienced leadership to develop or influence statistical modeling, analytical strategies, and advanced data visualization for complex business and technical needs.
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Strong database design and modeling knowledge deep understanding of data integrity and normalization. Mastery level SQL knowledge with minimum of 2 years of hands on experience ability to run analysis and complex SQLs against large sets of data is a must Preferably experience with Oracle DBMS.
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At least 3 years of experience in designing, implementing, and maintaining robust and scalable data pipelines on Azure using services such as Azure Data Factory, Azure SQL Data Warehouse, Azure Analysis Services or any of the Azure Databricks/Synapse/Fabric.
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Working knowledge of various statistical modeling techniques and their application within complex analytical projects, e.g., regression modeling, promotion response modeling, ROI, natural language processing, predictive modeling, etc.
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Expertise in statistical modeling, machine learning algorithms, and data mining techniques, with proficiency in programming languages such as Python, R, or SQL. Collaborate with data engineering and IT teams to ensure data accessibility, integrity, and scalability for analytics and modeling purposes.
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Familiarity with spreadsheets (VBA) and database applications (Access, Oracle, SQL, or equivalent technology). Familiarity with R or Python for predictive modeling. Knowledge of SQL and VBA.
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Emerging No-SQL and Azure Cloud DB approaches and challengesand how to model. Lead those that are not on our team to execute our standard Enterprise Data Modeling point-of-view. Thorough mastery of logical and physical data modeling.
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Experience with a broad range of database and business intelligence environments including: IBM Cognos, Power BI, Snowflake, Netezza, Oracle and SQL Server. Expert-level knowledge in designing and developing paginated reports and a business semantic layer using the Cognos stack, including Cognos Portal, Cognos data modeling, and TM1 integration.
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SSIS, Data Architecture and Modeling, SQL Server, ADF, Power BI. Strong SQL Server , SSIS ( or any ETL tool ), Strong knowledge on DWH concepts, Azure is mandatory With average skill set ( ADF, Databricks and Power BI.
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This candidate needs to use data analytics & modeling skills to analyze digital, operational, session replay, VOC, customer call center, and other data sources to deliver Insights that will improve digital experiences at UPS. He/She will need to understand how audiences are created in Adobe Audience Manager (DMP), and how to leverage these audiences for robust Insights.
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Strong programming skills in any of the following: SAS, SQL, R, Python. Strong analytical skills, especially in predictive modeling and data mining techniques. Conduct predictive modeling.
$81,400 - $85,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hands on Experience with : R, Python, SQL, AWS (EMR, EC2, Redshift, Athena, S3, Sage Maker) Responsible to analyze the trade / transaction monitoring alert from a trading platform and apply modern data science modeling techniques to predict future disputes & anomalies to proactively manage the risk.
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5+ years’ experience as a data scientist or in another predictive modeling job with specialization in machine learning, statistical modeling and optimization. Master’s degree in Data Science, Applied Economics, Statistics, or STEM field with sufficient overlap in explanatory analysis, predictive modeling, data treatments and coding.
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Experience with Apache Spark, Python, SQL, and/or R. Experience with using DataBricks, or another similar tool, to perform data transformations or modeling. Experience with Apache Spark, Python, SQL, and/or R.
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Expert-level experience developing in Oracle SQL Developer or ER/Studio Data Architect for Oracle. Provides documentation to support the Kimball Dimensional Data Modeling Framework. Expert-level Kimball Dimensional Data Modeling experience.
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