{"id":5791,"date":"2025-08-02T07:03:49","date_gmt":"2025-08-02T07:03:49","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/08\/02\/i-think-of-analysts-as-data-wizards-who-help-their-product-teams-solve-problems\/"},"modified":"2025-08-02T07:03:49","modified_gmt":"2025-08-02T07:03:49","slug":"i-think-of-analysts-as-data-wizards-who-help-their-product-teams-solve-problems","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/08\/02\/i-think-of-analysts-as-data-wizards-who-help-their-product-teams-solve-problems\/","title":{"rendered":"\u201cI think of analysts as data wizards who help their product teams solve problems\u201d"},"content":{"rendered":"<p>    \u201cI think of analysts as data wizards who help their product teams solve problems\u201d<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>Mariya Mansurova explains how hands-on learning, agentic AI, and engineering habits shape her writing and work.<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/i-think-of-analysts-as-data-wizards-who-help-their-product-teams-solve-problems\/\">\u201cI think of analysts as data wizards who help their product teams solve problems\u201d<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    TDS Editors<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/i-think-of-analysts-as-data-wizards-who-help-their-product-teams-solve-problems\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u201cI think of analysts as data wizards who help their product teams solve problems\u201d Mariya Mansurova explains how hands-on learning, agentic AI, and engineering habits shape her writing and work. The post \u201cI think of analysts as data wizards who help their product teams solve problems\u201d appeared first on Towards Data Science. TDS Editors Go [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3349,62,69,3236,83,82,279,70],"tags":[3399,84,268],"class_list":["post-5791","post","type-post","status-publish","format-standard","hentry","category-agentic","category-aimldsaimlds","category-artificial-intelligence","category-author-spotlights","category-data-science","category-data-visualization","category-interview","category-machine-learning","tag-analysts","tag-data","tag-think"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/5791"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=5791"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/5791\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=5791"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=5791"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=5791"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}