R (Language)
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Back in the late nineties, when statisticians apparently decided coding was cool, R emerged as a sort of open-source rebellion against the expensive, proprietary statistical packages dominating the landscape. It promised a flexible environment for data analysis, visualization, and, let’s be honest, a frankly alarming degree of customizability. The reality? It’s a bit like building a car from spare parts – incredibly powerful if you really know what you’re doing, but prone to unexpected breakdowns and requiring constant tinkering.
Compared to Python, which has become the darling of the machine learning crowd, R remains stubbornly focused on statistical computing. While Python strives for general-purpose dominance, R happily wallows in its niche, beloved by academics, biostatisticians, and anyone who enjoys wrestling with package dependencies. It’s still surprisingly relevant, powering much of the statistical rigor behind everything from clinical trials to financial modeling. Though one suspects many users are still running code written on floppy disks.
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| Marketing, Data Science, Computer Science, SAS, R, SPSS, Python, VBA, SQL, Data Modelling | |||
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BR | 2025-12-28
Agoda seeks a recent graduate capable of supporting data-driven marketing experiments across multiple search engines and social platforms. The role's differentiator lies in exposure to a global...
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Marketing, Data Science, Computer Science, SAS, R, SPSS, Python, VBA, SQL, Tableau | ||
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promoted
BigQuery Cost Optimization Guide by Masthead DataThe BigQuery Cost Optimization Guide is a valuable resource that offers a deep dive into understanding and managing the complexities of BigQuery costs. It provides practical guidelines and strategies to help you optimize both storage and compute expenses, ensuring you get the most value out of... |
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| Marketing, Data Science, Computer Science, SAS, R, SPSS, Python, VBA, SQL, Tableau | |||
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data engineer
Cientista de Dados / Híbrido - Rio de Janeiro/RJ @ capco
BR | 2025-12-27
This role requires extensive experience with data analysis and modeling in the oil and gas sector, emphasizing operational optimization, predictive maintenance, and asset monitoring. A key...
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Analytics, Python, R, SQL, AI/ML, PostgreSQL, SQL Server, NoSQL, MongoDB, Cassandra, ETL/ELT, Spark, Databricks, Cloud Computing, AWS, Azure, GCP, Big Data, Hadoop, Kafka, DevOps, MLOps, Docker, Kubernetes, Git, CI/CD, Agile/Scrum, Microsoft, Tableau, Grafana |