{"id":888,"date":"2020-02-12T19:31:27","date_gmt":"2020-02-12T14:01:27","guid":{"rendered":"https:\/\/cvdragon.com\/blog\/?p=888"},"modified":"2020-06-02T19:35:28","modified_gmt":"2020-06-02T14:05:28","slug":"prepare-data-scientist-interview","status":"publish","type":"post","link":"https:\/\/cvdragon.com\/blog\/prepare-data-scientist-interview\/","title":{"rendered":"How do I prepare for a data scientist interview?"},"content":{"rendered":"<p><strong>Technical interviews<\/strong> are <em>tough.<\/em> They need a lot of <em>preparation<\/em> as well as <em>practice<\/em> and there\u2019s no way around for it. You will need to have a <em>good understanding<\/em> <em>of<\/em> <em>data structures<\/em> and <em>algorithms<\/em> as you may be asked to design a model during the interview. A stronghold on <strong>Python<\/strong> and <strong>SQL<\/strong> is also preferred.<\/p>\n<p>Look for sites such as <strong>Leetcode<\/strong> where there are problems based on such concepts and practice as much as you can. Solving many problems will ensure you <em>learn new things<\/em> while also perfecting your current knowledge. There is obviously a chance that something you don\u2019t know might pop up in the interview as you can never stop learning things like this but focus on technology that the company uses and start building around that.<\/p>\n<p>Apart from the technical aspect, <em>try to fit the culture of the company<\/em> and you are good to go!<\/p>\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>Technical interviews are tough. They need a lot of preparation as well as practice and there\u2019s no way around for it. You will need to have a good understanding of data structures and algorithms as you may be asked to design a model during the interview. A stronghold on Python [&hellip;]<!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":1,"featured_media":1130,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[114],"tags":[50,309,135,9,36,33,272,311,310],"class_list":["post-888","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-queries","tag-crack-interview","tag-data-science","tag-data-scientist","tag-resume","tag-resume-errors","tag-resume-mistakes","tag-technical-skills","tag-technological-facts","tag-technology"],"_links":{"self":[{"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/posts\/888","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/comments?post=888"}],"version-history":[{"count":2,"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/posts\/888\/revisions"}],"predecessor-version":[{"id":1309,"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/posts\/888\/revisions\/1309"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/media\/1130"}],"wp:attachment":[{"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/media?parent=888"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/categories?post=888"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cvdragon.com\/blog\/wp-json\/wp\/v2\/tags?post=888"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}