{"id":486,"date":"2019-11-29T17:33:32","date_gmt":"2019-11-29T17:33:32","guid":{"rendered":"https:\/\/www.danielparente.net\/en\/2019\/11\/29\/what-data-scientists-do-and-how-to-work-with-them\/"},"modified":"2019-11-29T17:33:32","modified_gmt":"2019-11-29T17:33:32","slug":"what-data-scientists-do-and-how-to-work-with-them","status":"publish","type":"post","link":"https:\/\/www.danielparente.net\/en\/2019\/11\/29\/what-data-scientists-do-and-how-to-work-with-them\/","title":{"rendered":"What Data Scientists Do And How To Work With Them"},"content":{"rendered":"<p> [ad_1]<br \/>\n<\/p>\n<div _ngcontent-c17=\"\" innerhtml=\"&lt;figure class=&quot;embed-base image-embed embed-2&quot; role=&quot;presentation&quot;&gt;&lt;div&gt;&lt;img src=&quot;https:\/\/specials-images.forbesimg.com\/imageserve\/5de10e97ea103f000653ad60\/960x0.jpg?fit=scale&quot; alt=&quot;Learning to work with data scientists is a necessary skill for a successful career. &quot;  data-height=&quot;4463&quot;  data-width=&quot;7952&quot;&gt;&lt;\/div&gt;&lt;figcaption&gt;&lt;fbs-accordion&gt;&lt;p class=&quot;color-body light-text&quot;&gt;Learning to work with data scientists is a necessary skill for a successful career. &lt;\/p&gt;&lt;\/fbs-accordion&gt;&lt;small&gt;Getty&lt;\/small&gt;&lt;\/figcaption&gt;&lt;\/figure&gt;&lt;p&gt;Data is now said to be the new oil, making data scientists indispensable. However, it is still a fairly new field and many non-technical professionals do not have a clear understanding of what data scientists do, why they do it and how to work with them.&lt;\/p&gt;&lt;p&gt;When building a company that monetizes consumer behavior data, I knew we would need to involve data scientists. But as non-technical founder with a business background, I did not know when or how to hire them, or even how to present the problems we needed to solve. As often happens when non-technical people delve into the world of technology, there are plenty of unknown unknowns. How do you find an answer if you are not quite sure what the question is?&lt;\/p&gt;&lt;p&gt;I spoke to Susie Sun, data scientist at WhatsApp, about what data science is, what data scientists do and how business functions should work with them. Sun  understands both the commercial and the technical sides of the equation well, having started her career on the business side and completed an MBA at INSEAD, before transitioning to data science. &amp;nbsp;&lt;\/p&gt;&lt;figure class=&quot;embed-base image-embed embed-1&quot; role=&quot;presentation&quot;&gt;&lt;div&gt;&lt;img src=&quot;https:\/\/specials-images.forbesimg.com\/imageserve\/5de10cac755ebf0006fbbdd7\/960x0.jpg?cropX1=1691&amp;cropX2=3587&amp;cropY1=419&amp;cropY2=1842&quot; alt=&quot;Susie Sun, data scientist at WhatsApp&quot;  data-height=&quot;2400&quot;  data-width=&quot;3600&quot;&gt;&lt;\/div&gt;&lt;figcaption&gt;&lt;fbs-accordion&gt;&lt;p class=&quot;color-body light-text&quot;&gt;Susie Sun, data scientist at WhatsApp&lt;\/p&gt;&lt;\/fbs-accordion&gt;&lt;small&gt;Susie Sun&lt;\/small&gt;&lt;\/figcaption&gt;&lt;\/figure&gt;&lt;p&gt;Sun\u2019s definition of data science is \u201cusing the accidental output of computing - i.e. data - this new(ish) field uses statistics and coding to do previously difficult things, from understanding customer behavior, to making predictions, to copying human-like \u2018intelligence.\u2019\u201d&amp;nbsp;&lt;\/p&gt;&lt;div class=&quot;vestpocket&quot; vest-pocket&gt;&lt;\/div&gt;&lt;p&gt;Much like the term engineer, the term data science can encompass a broad spectrum. Sun suggests thinking about data scientists on the following spectrum:&lt;\/p&gt;&lt;figure class=&quot;embed-base image-embed embed-0&quot; role=&quot;presentation&quot;&gt;&lt;div&gt;&lt;img src=&quot;https:\/\/specials-images.forbesimg.com\/imageserve\/5de10b91ea103f000653ad49\/960x0.jpg?fit=scale&quot; alt=&quot;Data Scientists use a mix of business and technical skills to solve problems&quot;  data-height=&quot;730&quot;  data-width=&quot;893&quot;&gt;&lt;\/div&gt;&lt;figcaption&gt;&lt;fbs-accordion&gt;&lt;p class=&quot;color-body light-text&quot;&gt;Data Scientists use business and technical skills to solve problems&lt;\/p&gt;&lt;\/fbs-accordion&gt;&lt;small&gt;Sophia Matveeva and Susie Sun&lt;\/small&gt;&lt;\/figcaption&gt;&lt;\/figure&gt;&lt;p&gt;Giving an e-commerce business as an example, Sun presents the following divisions:&lt;\/p&gt;&lt;p&gt;&lt;ul&gt;&lt;li&gt;Data Analysts answer questions like&amp;nbsp;\u201cGiven this customer funnel data, where are my customers dropping off?\u201d The output is data.&lt;\/li&gt;&lt;li&gt;Data Scientists answer questions like \u201cGiven all my data, how can I improve profitability?\u201d The output of their work is insight.&amp;nbsp;&lt;\/li&gt;&lt;li&gt;Machine Learning engineers answer questions like \u201cGiven that I want to increase my customer basket size, how can I build or improve my recommendation engine?\u201d The output of their work is a model.&amp;nbsp;&lt;\/li&gt;&lt;\/ul&gt;&lt;\/p&gt;&lt;p&gt;Continuing with the e-commerce example, Sun says that data scientists can use information such as past sales transactions, customer details and demographic data to understand who the company\u2019s most valuable customers are. If you know this, you can adjust your marketing to target the people who are likely to spend the most with your business.&amp;nbsp;&lt;\/p&gt;&lt;p&gt;With machine learning and predictive analytics businesses can take these insights even further. If you know who your most valuable customers are based on the past interactions, you can build a model to spot similar customers early and tailor the e-commerce experience for them.&amp;nbsp;&lt;\/p&gt;&lt;p&gt;However, it is worth remembering that predictive analytics are based on past data, which does not make them entirely future proof. This is where data scientists, creatives and marketers can work together to combine data with instinct.&amp;nbsp;&lt;\/p&gt;&lt;p&gt;&lt;strong&gt;Hiring data scientists&lt;\/strong&gt;&lt;\/p&gt;&lt;p&gt;If you are considering hiring a data scientist, think about what questions your business is facing. Examples of questions that data scientists can answer include:&amp;nbsp;&lt;\/p&gt;&lt;p&gt;&lt;ul&gt;&lt;li&gt;How can I detect fraud before a purchase goes through?&lt;\/li&gt;&lt;li&gt;How do I match users to advertising in order to maximize my revenue?&lt;\/li&gt;&lt;li&gt;How can I better predict sales at each location so that we do not run out of stock?&lt;\/li&gt;&lt;\/ul&gt;&lt;\/p&gt;&lt;p&gt;An important point to consider is whether you have enough data for the data scientist to provide you real insights. This is why companies that collect their own data need exist for a while before getting a data scientist involved.&amp;nbsp;&lt;\/p&gt;&lt;p&gt;&lt;strong&gt;Working with data scientists&lt;\/strong&gt;&lt;\/p&gt;&lt;p&gt;To have the most productive relationship with a data scientist, present the problem and ask them to find a solution, rather than presenting your own. This is the same advice I would give about working with developers in general. It is not the business person\u2019s responsibility to understand the fine points of writing back end code, but it is up to them to gather customer feedback and work with their technical teams to make sure the product works.&lt;\/p&gt;&lt;p&gt;As every company becomes enabled by technology, and traditional businesses acquire technology companies, learning how to work with data scientists and other technical professionals is a necessary skill for a successful career.&amp;nbsp;&lt;\/p&gt;&lt;p&gt;Data may be the new oil, but if you do not know how to use it and work with people who do, it is just a collection of meaningless facts.&amp;nbsp;&lt;\/p&gt;\">\n<figure class=\"embed-base image-embed embed-2\" role=\"presentation\">\n<div><img decoding=\"async\" src=\"https:\/\/specials-images.forbesimg.com\/imageserve\/5de10e97ea103f000653ad60\/960x0.jpg?fit=scale\" alt=\"Learning to work with data scientists is a necessary skill for a successful career. \" data-height=\"4463\" data-width=\"7952\"\/><\/div><figcaption><fbs-accordion><\/p>\n<p class=\"color-body light-text\">Learning to work with data scientists is a necessary skill for a successful career. <\/p>\n<p><\/fbs-accordion><small>Getty<\/small><\/figcaption><\/figure>\n<p class=\"speakable-paragraph\">Data is now said to be the new oil, making data scientists indispensable. However, it is still a fairly new field and many non-technical professionals do not have a clear understanding of what data scientists do, why they do it and how to work with them.<\/p>\n<p>When building a company that monetizes consumer behavior data, I knew we would need to involve data scientists. But as non-technical founder with a business background, I did not know when or how to hire them, or even how to present the problems we needed to solve. As often happens when non-technical people delve into the world of technology, there are plenty of unknown unknowns. How do you find an answer if you are not quite sure what the question is?<\/p>\n<p>I spoke to Susie Sun, data scientist at WhatsApp, about what data science is, what data scientists do and how business functions should work with them. Sun  understands both the commercial and the technical sides of the equation well, having started her career on the business side and completed an MBA at INSEAD, before transitioning to data science. \u00a0<\/p>\n<figure class=\"embed-base image-embed embed-1\" role=\"presentation\">\n<div><img decoding=\"async\" src=\"https:\/\/specials-images.forbesimg.com\/imageserve\/5de10cac755ebf0006fbbdd7\/960x0.jpg?cropX1=1691&amp;cropX2=3587&amp;cropY1=419&amp;cropY2=1842\" alt=\"Susie Sun, data scientist at WhatsApp\" data-height=\"2400\" data-width=\"3600\"\/><\/div><figcaption><fbs-accordion><\/p>\n<p class=\"color-body light-text\">Susie Sun, data scientist at WhatsApp<\/p>\n<p><\/fbs-accordion><small>Susie Sun<\/small><\/figcaption><\/figure>\n<p>Sun\u2019s definition of data science is \u201cusing the accidental output of computing &#8211; i.e. data &#8211; this new(ish) field uses statistics and coding to do previously difficult things, from understanding customer behavior, to making predictions, to copying human-like \u2018intelligence.\u2019\u201d\u00a0<\/p>\n<p>Much like the term engineer, the term data science can encompass a broad spectrum. Sun suggests thinking about data scientists on the following spectrum:<\/p>\n<figure class=\"embed-base image-embed embed-0\" role=\"presentation\">\n<div><img decoding=\"async\" src=\"https:\/\/specials-images.forbesimg.com\/imageserve\/5de10b91ea103f000653ad49\/960x0.jpg?fit=scale\" alt=\"Data Scientists use a mix of business and technical skills to solve problems\" data-height=\"730\" data-width=\"893\"\/><\/div><figcaption><fbs-accordion><\/p>\n<p class=\"color-body light-text\">Data Scientists use business and technical skills to solve problems<\/p>\n<p><\/fbs-accordion><small>Sophia Matveeva and Susie Sun<\/small><\/figcaption><\/figure>\n<p>Giving an e-commerce business as an example, Sun presents the following divisions:<\/p>\n<ul>\n<li>Data Analysts answer questions like\u00a0\u201cGiven this customer funnel data, where are my customers dropping off?\u201d The output is data.<\/li>\n<li>Data Scientists answer questions like \u201cGiven all my data, how can I improve profitability?\u201d The output of their work is insight.\u00a0<\/li>\n<li>Machine Learning engineers answer questions like \u201cGiven that I want to increase my customer basket size, how can I build or improve my recommendation engine?\u201d The output of their work is a model.\u00a0<\/li>\n<\/ul>\n<p>Continuing with the e-commerce example, Sun says that data scientists can use information such as past sales transactions, customer details and demographic data to understand who the company\u2019s most valuable customers are. If you know this, you can adjust your marketing to target the people who are likely to spend the most with your business.\u00a0<\/p>\n<p>With machine learning and predictive analytics businesses can take these insights even further. If you know who your most valuable customers are based on the past interactions, you can build a model to spot similar customers early and tailor the e-commerce experience for them.\u00a0<\/p>\n<p>However, it is worth remembering that predictive analytics are based on past data, which does not make them entirely future proof. This is where data scientists, creatives and marketers can work together to combine data with instinct.\u00a0<\/p>\n<p><strong>Hiring data scientists<\/strong><\/p>\n<p>If you are considering hiring a data scientist, think about what questions your business is facing. Examples of questions that data scientists can answer include:\u00a0<\/p>\n<ul>\n<li>How can I detect fraud before a purchase goes through?<\/li>\n<li>How do I match users to advertising in order to maximize my revenue?<\/li>\n<li>How can I better predict sales at each location so that we do not run out of stock?<\/li>\n<\/ul>\n<p>An important point to consider is whether you have enough data for the data scientist to provide you real insights. This is why companies that collect their own data need exist for a while before getting a data scientist involved.\u00a0<\/p>\n<p><strong>Working with data scientists<\/strong><\/p>\n<p>To have the most productive relationship with a data scientist, present the problem and ask them to find a solution, rather than presenting your own. This is the same advice I would give about working with developers in general. It is not the business person\u2019s responsibility to understand the fine points of writing back end code, but it is up to them to gather customer feedback and work with their technical teams to make sure the product works.<\/p>\n<p>As every company becomes enabled by technology, and traditional businesses acquire technology companies, learning how to work with data scientists and other technical professionals is a necessary skill for a successful career.\u00a0<\/p>\n<p>Data may be the new oil, but if you do not know how to use it and work with people who do, it is just a collection of meaningless facts.\u00a0<\/p>\n<\/div>\n<p>[ad_2]<br \/>\n<br \/><a href=\"https:\/\/www.forbes.com\/sites\/sophiamatveeva\/2019\/11\/29\/what-data-scientists-do-and-how-to-work-with-them\/\" target=\"_blank\" rel=\"noopener\">Source link <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>[ad_1] Learning to work with data scientists is a necessary skill for a successful career. Getty Data is now said to be the new oil, making data scientists indispensable. However, it is still a fairly new field and many non-technical professionals do not have a clear understanding of what data scientists do, why they do [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":487,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","jetpack_post_was_ever_published":false},"categories":[1],"tags":[],"class_list":["post-486","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"blocksy_meta":[],"jetpack_featured_media_url":"https:\/\/e928cfdc7rs.exactdn.com\/info\/uploads\/sites\/3\/2019\/11\/What-Data-Scientists-Do-And-How-To-Work-With-Them.jpg?strip=all","jetpack_shortlink":"https:\/\/wp.me\/p2TFCd-7Q","jetpack_sharing_enabled":true,"jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/posts\/486","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/comments?post=486"}],"version-history":[{"count":0,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/posts\/486\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/media\/487"}],"wp:attachment":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/media?parent=486"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/categories?post=486"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/tags?post=486"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}