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by dtjones
2258 days ago
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I've been working in data roles for 10 years and hold a masters in ML. I've hired and managed each of the roles you mentioned. I think of the responsibilities of each of those roles as: -ML Engineers as building software infrastructure to scale machine learning inference and training. -Data engineers focusing on data infrastructure and pipelining into either model inference, training, or other business intelligence platforms -Analysts consume the product of the data engineer in the BI platform or excel, where the results would be consumed as a report in some form. -And ML Researchers would be those inventing novel machine learning algorithms to deploy in the ML Infrastructure managed by the ML Engineers -And data scientists to deploy well-known ML algorithms or statistical inference on varying datasets on the ML Infrascturue or as a slide deck. |
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