{"version":"1.0","provider_name":"insideBIGDATA","provider_url":"https:\/\/insidebigdata.com","author_name":"Editorial Team","author_url":"https:\/\/insidebigdata.com\/author\/editorial\/","title":"Mistakes to Avoid When Starting a Career in Data Science - insideBIGDATA","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"o0c5hFRJeW\"><a href=\"https:\/\/insidebigdata.com\/2021\/03\/13\/mistakes-to-avoid-when-starting-a-career-in-data-science\/\">Mistakes to Avoid When Starting a Career in Data Science<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/insidebigdata.com\/2021\/03\/13\/mistakes-to-avoid-when-starting-a-career-in-data-science\/embed\/#?secret=o0c5hFRJeW\" width=\"600\" height=\"338\" title=\"&#8220;Mistakes to Avoid When Starting a Career in Data Science&#8221; &#8212; insideBIGDATA\" data-secret=\"o0c5hFRJeW\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/*! This file is auto-generated *\/\n!function(c,d){\"use strict\";var e=!1,o=!1;if(d.querySelector)if(c.addEventListener)e=!0;if(c.wp=c.wp||{},c.wp.receiveEmbedMessage);else if(c.wp.receiveEmbedMessage=function(e){var t=e.data;if(!t);else if(!(t.secret||t.message||t.value));else if(\/[^a-zA-Z0-9]\/.test(t.secret));else{for(var r,s,a,i=d.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),n=d.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),o=new RegExp(\"^https?:$\",\"i\"),l=0;l<n.length;l++)n[l].style.display=\"none\";for(l=0;l<i.length;l++)if(r=i[l],e.source!==r.contentWindow);else{if(r.removeAttribute(\"style\"),\"height\"===t.message){if(1e3<(s=parseInt(t.value,10)))s=1e3;else if(~~s<200)s=200;r.height=s}if(\"link\"===t.message)if(s=d.createElement(\"a\"),a=d.createElement(\"a\"),s.href=r.getAttribute(\"src\"),a.href=t.value,!o.test(a.protocol));else if(a.host===s.host)if(d.activeElement===r)c.top.location.href=t.value}}},e)c.addEventListener(\"message\",c.wp.receiveEmbedMessage,!1),d.addEventListener(\"DOMContentLoaded\",t,!1),c.addEventListener(\"load\",t,!1);function t(){if(o);else{o=!0;for(var e,t,r,s=-1!==navigator.appVersion.indexOf(\"MSIE 10\"),a=!!navigator.userAgent.match(\/Trident.*rv:11\\.\/),i=d.querySelectorAll(\"iframe.wp-embedded-content\"),n=0;n<i.length;n++){if(!(r=(t=i[n]).getAttribute(\"data-secret\")))r=Math.random().toString(36).substr(2,10),t.src+=\"#?secret=\"+r,t.setAttribute(\"data-secret\",r);if(s||a)(e=t.cloneNode(!0)).removeAttribute(\"security\"),t.parentNode.replaceChild(e,t);t.contentWindow.postMessage({message:\"ready\",secret:r},\"*\")}}}}(window,document);\n<\/script>\n","thumbnail_url":"https:\/\/insidebigdata.com\/wp-content\/uploads\/2019\/05\/DataScience_SHUTTERSTOCK.jpg","thumbnail_width":250,"thumbnail_height":167,"description":"In this contributed article, IT and digital marketing specialist Natasha Lane, highlights how the shortage of data science talent is dramatic, but there are still a few mistakes you can make getting your foot in the door. These are the types of mistakes that can slow down your initial career progress, so the article covers them to help you make sure you\u2019ll avoid the pitfalls."}