{"id":15541,"date":"2018-10-24T00:00:00","date_gmt":"2018-10-23T23:00:00","guid":{"rendered":"https:\/\/members.dataiq.global\/articles\/hacking-data-find-missing-people-and-top-talent\/"},"modified":"2024-05-29T13:33:31","modified_gmt":"2024-05-29T12:33:31","slug":"hacking-data-find-missing-people-and-top-talent","status":"publish","type":"article","link":"https:\/\/www.dataiq.global\/devstage\/articles\/hacking-data-find-missing-people-and-top-talent\/","title":{"rendered":"Hacking data to find missing people and top talent"},"content":{"rendered":"

At the end of May, 22 data enthusiasts turned up at a building in the vicinity of Royal Mail\u2019s iconic Mount Pleasant sorting office in central London for a charity hackathon. Not only did this event have a philanthropic goal, but it brough Royal Mail into contact with bright and enthusiastic data talent. Royal Mail\u2019s head of data science, Ben Dias, and Wade Munsie, the director of advanced analytics and business intelligence development, spoke to Toni Sekinah about why hackathons are a good a way give something back and aid recruitment.<\/strong><\/p>\n

Two years ago Munsie set up the organisation\u2019s data team with just two people. A year later, Ben Dias joined as head of data science and took the size of the team to 20. Dias was then asked to double the size of the team to 40.<\/p>\n

Dias and Munsie had to think of a creative way to get more people into the team quickly – in March, the charity hackathon was a \u201ccrazy idea\u201d they came up with. But Rob Kent, Royal Mail\u2019s chief data officer, loved the idea. And so the charity hackathon took place on 24th<\/sup> May with a test dataset from the charity Missing People<\/a>.<\/p>\n

\n

“I want people who love what they are doing, not in it for the money.”<\/strong><\/h3>\n<\/blockquote>\n

\"GirlWhen asked why there was a charitable beneficiary of the hackathon, Dias said it was always part of the plan and important for two reasons. \u201cI don\u2019t want people in it for the money. I want people who love what they are actually doing,\u201d he said.<\/p>\n

The second reason is that it makes the participants feel like the time spent will be useful and of value to a charity. Dias said: \u201cIt feels less like we are getting them to do a day\u2019s work for free. It is going to a good cause.\u201d<\/p>\n

Munsie echoed this when he said: \u201cData scientists get a kick out of saving the world.\u201d Dias added that Royal Mail does a lot of charity work and Missing People is one of its charitable partners.<\/p>\n

\n

“Flexibility and adaptability are important.”<\/strong><\/h3>\n<\/blockquote>\n

However, Dias said that there were several other attributes that he would be looking for in a prospective employee. While he expected everybody to have a model that worked, accuracy would be as important as the candidate\u2019s way of working, their ability to collaborate, and their ability to pick up new concepts quickly.<\/p>\n

He said: \u201cA lot of people will be using virtual machines in Azure for the first time. If I allow them to take the data on their laptops, they would fly, but I want to see how quickly they adapt, giving them a new environment and new instructions. Flexibility and adaptability are important.\u201d<\/p>\n

\n

“Let the hypothesis be driven by the data.”<\/strong><\/h3>\n<\/blockquote>\n

\"PostThe day began with the information and evaluation officer at the charity, Jenny Dickson, telling the attendees that the more that is known about the reasons for people going missing, the more that can be done to help avoid it happening in the first place.\u00a0<\/p>\n

Then Royal Mail\u2019s deputy head of data science, Kat James, gave the attendees some contextual information about the test dataset of 4,500 individuals from one British city they would be working with. She said that the aim of the day would be to create a model that could correctly identify the indicators that flag an individual as more likely to go missing.<\/p>\n

James said that the models would be assessed on two innovation metrics: recall and precision. Dias told them that he wanted them to use a hypothesis-driven approach and to \u201clet the hypothesis be driven by the data.\u201d<\/p>\n

Some members of the current Royal Mail data team were stationed at each table, while others floated around the room to help provide guidance and support to the attendees, though they were under strict instructions not to do any coding. However, they were also there in the capacity of assessors.<\/p>\n

“We needed to try and recruit almost in bulk.”<\/strong><\/h3>\n

Munsie said that they would be looking at the attendees\u2019 communication skills, problem-solving processes, the way they understand problems, their approach to data \u2013 be it focused or scattergun. The day after the hackathon, he and Dias would be scoring the candidates on those different traits, going over their CVs and assessing their overall suitability.<\/p>\n

Royal Mail worked with two partners and sponsors on the day\u2019s event; Logikk<\/a>, a recruitment firm that provided marketing and registration support, and Microsoft, which provided tech support. Dias said that he has a good working relationship with Logikk, as it was that company that recruited him to his current position.<\/p>\n

\"TeamMunsie went into more detail as to why the data team at Royal Mail<\/a> needed to be more creative with its recruitment strategy. \u201cWe needed to try and recruit almost in bulk. We were going to run a traditional assessment centre but we thought, \u2018There\u2019s got to be a better way,\u2019 and we came up with this.\u201d<\/p>\n

Proof of the success of the concept is that, following the hack, all the open positions in the team were filled. The hackathon achieved its aim despite the challenging market for data professionals that Royal Mail is competing in.<\/p>\n

Both Dias and Munsie said that good and available data candidates do not hang around in the market for long, such is the demand for them. Munsie also said that there is no official qualifications, industry standard or programming standard for the data industry.\u00a0<\/p>\n

“I like seeing them get their geek on.”<\/strong><\/h3>\n

This poses a serious challenge to Dias who may find himself having to choose between two candidates who both describe themselves as data scientists, but have completely different skillsets and tools that they have experience of.<\/p>\n

On top of that success, for Munsie it was an enjoyable experience. He said: \u201cI like seeing them get their geek on. I like seeing them working together and solving problems.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

At the end of May, 22 data enthusiasts turned up at a building in the vicinity of Royal Mail\u2019s iconic Mount Pleasant sorting office in central London for a charity hackathon. Not only did this event have a philanthropic goal, but it brough…<\/p>\n","protected":false},"author":3,"featured_media":15546,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"categories":[129,398],"tags":[167],"pillar":[],"class_list":["post-15541","article","type-article","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-public","tag-organisation-and-culture"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 06:46:24","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/15541","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/article"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=15541"}],"version-history":[{"count":0,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/15541\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/15546"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=15541"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=15541"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=15541"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=15541"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}