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Full stack software engineering experience, with proven experience in data visualization modules or frameworks like Python Dash and R Shiny. Solid software development skills including experience in R, Python and SQL. Knowledge of Database design and query optimization a plus.
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Hands on experience with programming for extract transform operations and data analysis using languages such as, but not limited to R, Python, SQL, and Excel VBA. Experience in developing data visualization and business intelligence solutions using tools such as, but not limited to, Shiny, Tableau, PowerBI, and front-end technologies and languages.
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Experience in developing Data Warehouse/Data Marts using, as examples, OBIEE, OBI APPS, Cognos, Business Objects, SPSS, SSIS, SSRS, Informatica Power Center, OWB and ODI. · Experience on design and development of Data Warehouse Architecture for Enterprise Data Warehouse (EDW), Operational data Store (ODS), Operational Data Marts and Data Marts.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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The successful candidate must demonstrate strong background in technology, data analytics, software development, and programming languages such as R, Python and SQL, with expertise in Business Intelligence tools (Shiny, Tableau, PowerBi.
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Proficiency in a coding language used for statistics and data science programming such as Python or R. Current PhD Student in Quantitative Discipline related to Data Science, including but not limited to Statistics, Mathematics, Economics, Computer Science, etc.
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6 to 8 years of experience with Data Analytics, KPI development and measurement generating analytical insights to drive business actions. You have working knowledge of analytic technologies (e.g. Alteryx, SAS, SQL, R, Python, Power BI, Tableau, Adobe Analytics, etc.
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Business Development: Collaborate with Sia Partner’s US Data Science Lead, Business Units teams, and Data Science centers from other locations to develop proposals for potential opportunities.
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You must be passionate about data management with a solid background in AWS, Databricks, Python, Trino/Starburst, Databases and SQL.Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms.
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Python, R and visualization tools (PowerBI and React) Nice to have - Post-graduate qualifications in computer science, data engineering or related. Lead and manage engineering projects in collaboration with other team members (including with offshore talent partners) to ensure rapid development of quality, scalable and sustainable data solutions, with global best practices and consistency.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Proficiency in analytical tools: modeling and reporting in Excel/Access and SQL Proficiency in data visualization tools: R, Python, Tableau, or similar. Act as a subject matter expert in marketing measurement science, specifically MMM + MTA unified-model measurement and media KPIs. Remain aware of data inconsistencies and work with IT, Tapestry Data Labs, Tapestry COE and/or the brand’s Agency of Record to ensure data efficacy & quality.
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Proficiency in programming languages and tools such as Python, R, SQL, MATLAB, C. Proficiency using leading software vendors for financial data and fixed income modeling, including Bloomberg, Aladdin, Intex, Trepp, and others.
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And health interoperability standards (HL7, FHIR, USCDI) preferred Experience working with real-world data sources such as EHR and claims data Familiarity (able to mostly read) with common data analysis tools and platforms (e.g., SQL, Python, R.
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