數據科學崗位將在十年後消失？

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據科學家會失業嗎?"}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"},{"type":"strong"}],"text":"本文最初發表在 InfoWorld，經 InfoWorld 授權，InfoQ 中文站翻譯並分享。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"AutoML 正在準備把開發人員變成數據科學家，反之亦然。本文闡述了 AutoML 將如何從根本上改進數據科學，使之變得更好。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"我們所知的數據科學家的角色在下一個十年將與現在有很大的不同，但是別擔心，沒有人預測數據科學家會失業，他們只不過是換了工作而已。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據科學家們不會有問題的：據美國勞工統計局（Bureau of Labor Statistics，BLS）的數據顯示，到 2029 年，這一角色仍將"},{"type":"link","attrs":{"href":"https:\/\/www.bls.gov\/ooh\/computer-and-information-technology\/computer-and-information-research-scientists.htm","title":"","type":null},"content":[{"type":"text","text":"以高於平均水平的速度增長"}]},{"type":"text","text":"。但是，技術的進步將使數據科學家的職責以及商業分析的整體方式發生重大變化。而"},{"type":"link","attrs":{"href":"https:\/\/www.infoworld.com\/article\/3430788\/automated-machine-learning-or-automl-explained.html","title":"","type":null},"content":[{"type":"text","text":"AutoML 工具"}]},{"type":"text","text":"將引領這場革命，它將幫助機器學習管道從原始數據到可用模型實現自動化。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"十年後，數據科學家將會擁有完全不同的技能和工具，但是他們的作用仍然保持不變：他們作爲有信心、有能力的技術指導者，能夠理解複雜的數據以解決問題。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"AutoML 使數據科學民主化"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"直到最近，"},{"type":"link","attrs":{"href":"https:\/\/www.infoworld.com\/article\/3394399\/machine-learning-algorithms-explained.html","title":"","type":null},"content":[{"type":"text","text":"機器學習算法"}]},{"type":"text","text":"和過程幾乎完全是更傳統的數據科學角色的領域：那些受過正規教育、擁有高等學歷，或者在大型科技公司工作的人。在機器學習開發領域的每個環節，數據科學家都扮演着重要的角色。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}