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O Programming Language: Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting. Use programming languages including but not limited to Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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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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Working knowledge of data visualization software such as Tableau, Looker, or Domo. - Advanced knowledge of data visualization software such as Tableau, Looker, or Domo. - Advanced knowledge of R, SQL, and Python.
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Knowledge of SQL, VBA, SAS, R, Python, ETL tools or Business Rules Engines is a plus, as is fluency in cloud databases and workflow scripts (e.g. Jupyter Notebooks) · Background experience in Tableau, Power BI, ThoughtSpot, Spotfire, COGNOS, or other data visualization software would be advantageous.
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Familiarity with data security principles and practices· Experience with data visualization tools (e.g., Tableau, Power BI) and statistical analysis tools (e.g., R, Python.
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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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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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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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T h e Developer w ill w o rk cl o s ely wi t h proje c t m a n a g ers, I T s t af f , p r o g ram s t aff a n d o t h er s t akeh o l d e rs t o defi n e a n d d e v e l o p r eq u ire m ents f o r the enterprise data warehouse.
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We use BigQuery here at MailchimpExpertise in visualization technologies like Looker, Tableau, or Qlik SenseExperience with GCP/AWS or other cloud providers is preferredFamiliarity with Python, Go, Java or another OOP language.
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Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques. Collaborating closely with various subject matter experts across various fields, our team leverages advanced statistical analysis, machine learning techniques, and data visualization tools to uncover patterns, trends, and correlations within the data.
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Advanced data analytics designing and building solutions using technologies such as Azure Data Factory, Azure Data Lake, HD Insights, SQL DWH, Stream Analytics, Machine Learning, R Server, Synapse, Azure Machine Learning (AML), Azure Kubernetes Service (AKS) for model deployments, Vector and Retrieval-Augmented Generation (RAG) implementation.
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Knowledge of coding and programming skills, including but not limited to Bloomberg, FactSet, Python, R, or equivalent. Experience managing and analyzing large data sets using data science tools such as artificial intelligence and machine learning.
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