{"id":40852,"date":"2026-02-03T17:26:21","date_gmt":"2026-02-03T17:26:21","guid":{"rendered":"https:\/\/www.dataiq.global\/?post_type=100-alumni&#038;p=40852"},"modified":"2026-02-04T14:15:28","modified_gmt":"2026-02-04T14:15:28","slug":"aydin-sheibani-chief-data-officer-hmrc","status":"publish","type":"100-alumni","link":"https:\/\/www.dataiq.global\/devstage\/dataiq100\/aydin-sheibani-chief-data-officer-hmrc\/","title":{"rendered":"Aydin Sheibani, Chief Data Officer, HMRC"},"content":{"rendered":"<p><span data-contrast=\"none\">Aydin\u00a0Sheibani\u00a0is Chief Data Officer at HM Revenue and Customs, where he is accountable for the department\u2019s enterprise-wide data strategy, governance, controls, and data solution delivery. He leads the development of HMRC\u2019s data science capability, ensuring it is embedded within the organisation\u2019s delivery lifecycle, and\u00a0is responsible for\u00a0defining and maintaining HMRC\u2019s data model and standards to enable more effective use of data across systems.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"none\">An accomplished public-sector leader, Aydin has extensive experience building high-performing, multidisciplinary teams and leading large-scale transformation programmes. He brings a results-driven, logical, and methodical approach, underpinned by strong strategic vision and a clear focus on long-term outcomes. A mathematics graduate, his career spans complex, regulated environments including transport, health, and utilities.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"none\">Prior to joining HMRC in 2021, Aydin was Head of Data Transformation at the Department for Work and Pensions, where he led a diverse team of programme managers, data scientists, developers, and product owners to transform service delivery and strengthen data culture across the department. Before this, he spent more than a decade at Transport for London, including as Head of Benchmarking, Value, and Insight. In that role, reporting to the Finance Director, he led a department of around 70 specialists, supporting London Underground\u2019s \u00a38 billion efficiency programme,\u00a0establishing\u00a0enterprise risk management, and improving organisational performance through insight drawn from world-class organisations.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Aydin\u00a0Sheibani\u00a0is Chief Data Officer at HM Revenue and Customs, where he is accountable for the department\u2019s enterprise-wide data strategy, governance, controls, and data solution delivery. He leads the development of HMRC\u2019s data science capability, ensuring it is embedded within the organisation\u2019s delivery lifecycle, and\u00a0is responsible for\u00a0defining and maintaining HMRC\u2019s data model and standards to enable [&hellip;]<\/p>\n","protected":false},"author":19,"featured_media":40869,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"100-designation":[1454],"100-search-term":[1456],"class_list":["post-40852","100-alumni","type-100-alumni","status-publish","format-standard","has-post-thumbnail","hentry","100-designation-100-brands-2026-europe","100-search-term-2026-europe-brands"],"acf":{"sort":"","rank":"","forename":"Aydin","surname":"Sheibani","fullname":"Aydin Sheibani","jobtitle":"Chief Data Officer ","organisation":"HMRC ","introduction":"","content_2":"","content_3":"","content_4":"","100_thumbnail_image":40869,"affinoid":""},"publishpress_future_action":{"enabled":false,"date":"2026-05-27 07:29:27","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"100-designation","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni\/40852","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/100-alumni"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=40852"}],"version-history":[{"count":3,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni\/40852\/revisions"}],"predecessor-version":[{"id":40870,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-alumni\/40852\/revisions\/40870"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/40869"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=40852"}],"wp:term":[{"taxonomy":"100-designation","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-designation?post=40852"},{"taxonomy":"100-search-term","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/100-search-term?post=40852"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}