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le parcours d'Aline, Data Analyst chez Patagonia, et mettez toutes les chances de votre c\u00f4t\u00e9 pour d\u00e9crocher un job \u00e0 impact.","_yoast_wpseo_title":null,"contenu_de_larticle":"57% des Fran\u00e7ais(es) veulent s\u2019engager dans un job qui r\u00e9pond aux enjeux environnementaux. Alors, comment d\u00e9crocher le fameux poste qui permettra de concilier vos engagements et votre vie professionnelle ?\r\n\r\nD\u00e9couvrez le parcours inspirant d\u2019Aline, Data Analyst chez Patagonia. D\u2019abord ing\u00e9nieure agronome, puis b\u00e9n\u00e9vole \u00e0 la Croix-Rouge en passant par une exp\u00e9rience en startup, elle vous racontera comment elle a fini par d\u00e9crocher le job de ses r\u00eaves et vous donnera de pr\u00e9cieux conseils pour arriver \u00e0 votre objectif.\r\n\r\n \r\n
J\u2019adorais faire des graphiques et je voulais faire \u00e7a toute la journ\u00e9e, mais je ne savais pas que c\u2019\u00e9tait un m\u00e9tier \u00e0 part enti\u00e8re.<\/blockquote>\r\nJ\u2019ai commenc\u00e9 en faisant des MOOC<\/strong> pour me donner des pistes sur ces m\u00e9tiers, et c\u2019est comme \u00e7a que j\u2019ai d\u00e9couvert le logiciel Tableau. Je me suis donc lanc\u00e9e en apprenant par moi-m\u00eame, via les MOOC (CodeAcademy<\/a>, DataCamp<\/a>, Coursera).\r\n\r\nSur Twitter, j\u2019ai trouv\u00e9 une communaut\u00e9 d\u2019utilisateurs de Tableau qui m\u2019a permis de d\u00e9couvrir un social data project :<\/strong> Makeover Monday<\/a>. Chaque dimanche, un nouveau jeu de donn\u00e9es \u00e9tait mis \u00e0 disposition et on devait en faire une visualisation avec Tableau. J\u2019ai beaucoup appris gr\u00e2ce \u00e0 \u00e7a, et, surtout, je me suis construit un portfolio solide sur Tableau Public<\/a><\/strong>. Il m\u2019a servi longtemps, jusqu\u2019\u00e0 mes entretiens pour Patagonia ! J\u2019ai fait des graphiques sur tellement de sujets qu\u2019il y en a toujours un qui marquait les lecteurs de mon CV : le Street Art, David Bowie, le sport, mes lectures\u2026\r\n\r\n \r\nQuel a \u00e9t\u00e9 ta premi\u00e8re \u201cvraie\u201d exp\u00e9rience dans la data ?<\/h3>\r\nJ\u2019ai commenc\u00e9 en tant que b\u00e9n\u00e9vole \u00e0 la Croix-Rouge, en tant que cartographe, puis en visualisation de donn\u00e9es. J\u2019ai ensuite eu un premier \u201cvrai emploi\u201d chez The Information Lab en tant que Consultante Tableau\/Alteryx<\/strong>, puis dans une startup en tant que Data Visualisation Specialist<\/strong>. Cette exp\u00e9rience co\u00efncidait davantage avec mes valeurs puisque la mission de cette organisation \u00e9tait d\u2019utiliser l\u2019IA pour detecter la fraude et le blanchiment d\u2019argent.\r\n\r\n \r\n
Que tires-tu de ces deux exp\u00e9riences ?<\/h3>\r\nEn tant que consultante<\/strong>, j\u2019ai travaill\u00e9 sur des projets tr\u00e8s vari\u00e9s et \u00e7a a \u00e9t\u00e9 tr\u00e8s enrichissant, tant sur l\u2019aspect personnel que sur mon CV. En plus, avec des missions entre 6 mois ou quelques jours, on se d\u00e9veloppe un bon r\u00e9seau<\/strong>. Cela m\u2019a \u00e9galement permis de savoir ce que j\u2019aimais<\/strong> : j\u2019ai travaill\u00e9 avec beaucoup de soci\u00e9t\u00e9s dont les valeurs ne me correspondaient pas, et c\u2019est ce qui \u00e9tait le plus dur pour moi. Le jour o\u00f9 j\u2019ai eu un petit projet avec Greenpeace, j\u2019ai \u00e9t\u00e9 tr\u00e8s heureuse !\r\n\r\nAu sein d\u2019une startup de deux ans, avec m\u00eame pas 20 collaborateurs, il y avait tout \u00e0 faire d\u2019un point de vue visualisation des donn\u00e9es. J\u2019ai tout commenc\u00e9 de z\u00e9ro, avec Tableau, c\u2019\u00e9tait tr\u00e8s challengeant mais j\u2019avais beaucoup de libert\u00e9s<\/strong>. J\u2019ai aussi beaucoup appris en travaillant avec les data engineers.\r\n\r\n \r\n
Et aujourd\u2019hui, quel est ton r\u00f4le chez Patagonia ?<\/h3>\r\nJe suis Data Analyst au sein de l\u2019\u00e9quipe Analytics and Insights<\/strong>, dans laquelle nous sommes quatre. On est un peu au centre du bureau puisqu\u2019on s\u2019occupe de plusieurs projets, tous diff\u00e9rents les uns des autres, mais toujours dans l\u2019analyse et la visualisation de donn\u00e9es pour aider les \u00e9quipes internes<\/strong>.\r\n\r\n \r\n
Peux-tu nous donner des exemples de projets sur lesquels tu travailles ?<\/h3>\r\nQuand vous achetez un produit chez Patagonia, vous avez l\u2019opportunit\u00e9 de le retourner et de le faire r\u00e9parer gratuitement. Il y a donc un d\u00e9partement \u201cRepair\u201d<\/strong> chez Patagonia, et c\u2019est un gros poste pour l\u2019entreprise. Ce syst\u00e8me de r\u00e9paration<\/strong> fonctionne notamment \u00e0 travers un formulaire en ligne o\u00f9 les personnes expliquent quel produit elles souhaitent faire r\u00e9parer, quel est le probl\u00e8me sur le produit en question, etc.\r\n\r\nCe p\u00f4le, bien qu\u2019il ne rapporte pas d\u2019argent \u00e0 Patagonia, manquait de vision : beaucoup de questions se posaient, pour des donn\u00e9es quasi inexistantes. L\u2019un de mes projets a donc \u00e9t\u00e9 de collecter les donn\u00e9es derri\u00e8re ces formulaires, plus de 20 tables, de trouver les cl\u00e9s pour les joindre avec Snowflake et SQL. L\u2019objectif du projet \u00e9tait d\u2019obtenir un dataset propre, pour faire un rapport r\u00e9pondant aux questions de l\u2019\u00e9quipe Repair, par exemple:<\/strong> quels produits a \u00e9t\u00e9 le plus r\u00e9par\u00e9 cette ann\u00e9e ? Pour quelles raisons ?\r\n\r\nUn autre exemple : la marque Patagonia est vendu dans d\u2019autres magasins (Le Vieux Campeur, par exemple). Ces revendeurs d\u00e9couvrent et ach\u00e8tent en r\u00e9alit\u00e9 nos collections 1 an \u00e0 l\u2019avance, \u00e0 la suite de r\u00e9unions organis\u00e9es par l\u2019\u00e9quipe Wholesale. L\u2019un des projets sur lequel j\u2019ai collabor\u00e9 \u00e9tait de r\u00e9cup\u00e9rer les donn\u00e9es du syst\u00e8me de vente pour visualiser les pr\u00e9visions d\u2019achat et aider les Sales \u00e0 se rendre compte de leur progression<\/strong> par rapport \u00e0 leurs objectifs. Je ne suis jamais seule sur les projets, c\u2019est toujours une collaboration avec les utilisateurs finaux et les data engineers.\r\n\r\n \r\n
Quels sont tes projets pour la suite ?<\/h3>\r\nJ\u2019envisage de rester \u00e0 mon poste, tout est encore tres nouveau pour moi. C\u2019\u00e9tait vraiment mon dream job ! Si je devais<\/em> changer, je resterais dans la data, peut-\u00eatre plus dans les donn\u00e9es li\u00e9es \u00e0 l\u2019environnement.\r\n\r\n \r\n
Quels conseils donnerais-tu pour d\u00e9crocher le job de ses r\u00eaves ?<\/h3>\r\nPr\u00e9parez au maximum vos entretiens, en vous renseignant sur la mission de l\u2019entreprise<\/strong>. Pour avoir \u00e9t\u00e9 recruteuse, je trouve laborieux de devoir absolument tout r\u00e9expliquer. Si vous \u00eates vraiment int\u00e9ress\u00e9(e) par le poste, donnez vous au maximum sur les \u00e9tudes de cas mais insistez pour la pr\u00e9senter plut\u00f4t que l\u2019envoyer<\/strong> : cela donne une occasion de d\u00e9fendre son travail et d\u2019expliquer son raisonnement.\r\n\r\nEnfin, lorsque vous vous prenez de passion pour quelque chose de pr\u00e9cis, parlez-en autour de vous<\/strong>. Les gens retiennent ce qui vous passionnent, et quand il y a une opportunit\u00e9, parfois inattendue, elle est pour vous !\r\n\r\n \r\n\r\n \r\n\r\nMerci Aline !\r\n\r\n","_contenu_de_larticle":"field_6412588b55814","titre_de_la_banniere":"","_titre_de_la_banniere":"field_6422eb732c237","paragraphe_de_la_banniere":"","_paragraphe_de_la_banniere":"field_6422ed834a968","intitule_du_bouton_de_la_banniere":"","_intitule_du_bouton_de_la_banniere":"field_6422ed934a969","lien_du_bouton_de_la_banniere":"","_lien_du_bouton_de_la_banniere":"field_6422eda54a96a","yoast_head":"\n
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