{"id":179461,"date":"2018-06-05T16:00:09","date_gmt":"2018-06-05T16:00:09","guid":{"rendered":"https:\/\/www.smartdatacollective.com\/?p=179461"},"modified":"2018-06-05T13:15:20","modified_gmt":"2018-06-05T13:15:20","slug":"learn-leading-data-scientists","status":"publish","type":"post","link":"https:\/\/www.smartdatacollective.com\/learn-leading-data-scientists\/","title":{"rendered":"4 Crucial Qualifications Data Scientists Need to Thrive"},"content":{"rendered":"

Data scientists have a prominent job. They are essential to every industry and just about everyone who loves data wants their job. Sometimes, they seem like magicians. When you pull back the curtain, of course, they\u2019re just people\u2014very smart people. If you\u2019re feeling stuck in your career, take these four lessons from leading data scientists<\/a> so that one day, you can get a job as a data scientist.<\/p>\n

1. Failure Shouldn\u2019t Be Feared<\/strong><\/h2>\n

It\u2019s an interesting paradox: just about all of us fear failure. At the same time, failure is the best teacher and is often inevitable to our future success.\u00a0 Jo\u00e3o Marcos Gris failed many times when he first tried to land a data science role after getting a BSc degree in Computer Engineering. Getting turned down (failing) taught him to seek feedback and learn from failure to ultimately get the results he wanted. His thoughts on the process:<\/p>\n

\u201cI really felt that this experience was very enriching for me, despite being a very tiring one also. I\u2019ve made a lot of mistakes along the way and tried to improve myself for each and every one of the applications that I did.\u201d<\/p><\/blockquote>\n

Turning your failures into learning experiences is the only way to grow and achieve your goals.<\/p>\n

2. Don\u2019t Be Afraid to Go Back to School<\/strong><\/h2>\n

Steve Mills of Booz Allen Hamilton notes that being a data scientist isn\u2019t just about crunching the numbers. He emphasizes the need to think creatively and artistically, even in a highly mathematical and analytical field like data science. Data scientists, Mills says<\/a>, \u201caren\u2019t just computer nerds.\u201d They need to have communications, curiosity and creativity. Sometimes, cultivating that creativity takes a little nudge.<\/p>\n

If you feel like you\u2019re stuck in a rut, it may be time to think about reinvesting in your education. If you\u2019ve always been logical, try some creative classes. Explore a new career. Going back to school may help you expand your knowledge and thinking, give you a new perspective, specialize your skills<\/a>, improve your resume, develop a larger network, and advance your career.<\/p>\n

3. Stay Driven <\/strong><\/h2>\n

\u00a0<\/strong>It\u2019s not always easy to keep up motivation when you\u2019re tired or discouraged. The journey doesn\u2019t stop when you reach your ideal job, however. You need to stay humble and driven\u2014always asking the next question and pushing yourself to be better. The world doesn\u2019t stand still, and neither should you\u2014you should always be seeking knowledge from others and adapting to the world around you.<\/p>\n

Bill Schmarzo says that one of the first skills he looks for when hiring data scientists is humility<\/a>. It is even more important than skill. He knows that people who maintain humility work better in teams and are always going to stay driven, trying to constantly improve themselves and their work. He also sees it as the biggest factor in creating a strong hypothesis\u2014absolutely crucial for data scientists.<\/p>\n

4. Learn to Leverage the Unlimited Potential of Data <\/strong><\/h2>\n

\u00a0<\/strong>Former Chief Data Officer DJ Patil \u00a0has jumped around from a number of positions ranging from LinkedIn to Ebay to professor to government official\u2014all thanks to both the rise of data and his ability to leverage its potential to create new opportunities.<\/p>\n

He also has a remarkable ability to discover innovative solutions to problems<\/a>. During his first year as a graduate student, he asked administrators for access to the computer lab (off-limits then to first-year grad students). They denied his request, but he was determined. So he went straight to one of the professors and asked how he might get computer access. The man who would become his mentor gave him a note, and the administrators reluctantly granted him access to the computer lab.<\/p>\n

It\u2019s clear that Patil has used that approach of applying creative solutions to nearly everything he does. You need creativity and drive to leverage the nearly unlimited power of data. Today, we\u2019re seeing just how powerful it can be in almost every sector even criminal justice<\/a>. No matter what your ideal career path may be, there\u2019s almost certainly some way to use data to your advantage\u2014you just can\u2019t take no for an answer.<\/p>\n","protected":false},"excerpt":{"rendered":"

Data scientists have a prominent job. They are essential to every industry and just about everyone who loves data wants their job. Sometimes, they seem like magicians. When you pull back the curtain, of course, they\u2019re just people\u2014very smart people. If you\u2019re feeling stuck in your career, take these four lessons from leading data scientists […]<\/p>\n","protected":false},"author":966,"featured_media":268820,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_seopress_robots_primary_cat":"2661","_seopress_titles_title":"4 Crucial Qualifications Every Data Scientist Need to Thrive","_seopress_titles_desc":"Data science is an exciting and rewarding career, but it is also very challenging. Here's what you need to thrive in this challenging field.","_seopress_robots_index":"","footnotes":""},"categories":[2661],"tags":[937,954,2795],"class_list":{"0":"post-179461","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"tag-data-science","9":"tag-data-scientists","10":"tag-personal-growth"},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/posts\/179461","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/users\/966"}],"replies":[{"embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/comments?post=179461"}],"version-history":[{"count":3,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/posts\/179461\/revisions"}],"predecessor-version":[{"id":268821,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/posts\/179461\/revisions\/268821"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/media\/268820"}],"wp:attachment":[{"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/media?parent=179461"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/categories?post=179461"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.smartdatacollective.com\/wp-json\/wp\/v2\/tags?post=179461"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}