R (Language)

programming language, statistical computing, data analysis
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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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9959

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analytics engineer

Geography Content Group Manager - Content Management Office, Travel & Mobility Business (C&M) @ rakuten

JP | 2025-12-26
Rakuten Travel seeks a Manager for the Geography Content Group to own geospatial data quality, localization, and global POI strategy for an English-first Rakuten Travel experience. You lead a... read more »
SQL, AI/ML, Marketing, Management, GIS, DataViz, Python, R, JavaScript, Jira, Tableau, Power BI
analytics engineer

【1496】_TE_【東京勤務】Honda SDV開発におけるデータ基盤エンジニア／データサイエンティスト @ honda

JP | 2025-12-25 | JPY 5900000 - 1090000 / year
Honda is fervently pursuing its Software Defined Vehicle (SDV) initiative, seeking a data engineer to architect and construct a robust data foundation from their labyrinthine data source web.... read more »
AI/ML, ETL/ELT, Python, SQL, JavaScript, C, AWS, Redshift, AWS Glue, AWS Lambda, GCP, BigQuery, Dataflow, Azure, Synapse, Databricks, Docker, Kubernetes, Jenkins, GitHub, GitLab, Jira, Confluence, Tableau, Power BI, Superset, Pandas, TensorFlow, PyTorch, GenAI, R, CI/CD