Love data and wondering how you could get into a role in FinTech, Robotics or even Policing? 那么数据科学的职业生涯可能会适合你. 有这么多的机会, it's no wonder why it's becoming a buzzword amongst companies looking to hire tech talent.
多年来, 我们中的许多人都成功地掌握了Excel和Tableau, 但数据技术正在以惊人的速度发展, with Data Science being one of the most exciting emerging jobs in the tech sector, 根据一份来自 LinkedIn. At hackajob, 我们经常看到数据科学方面的职位出现, 虽然很多人都听说过, 并不是所有人都知道它的目的和过程.
那么数据科学到底是什么呢?
Data science is interdisciplinary which means it makes use of various processes, 编程, 科学的方法, systems and even algorithms to extract knowledge and insights from many structural and unstructured data. This knowledge of interconnecting disciplines makes those who are in the field very attractive to
If you're an enthusiast looking to break into the world of Data Science, 这里有5条建议可以帮助你开始.
1. 热爱学习
If you’re a curious person who loves to learn, Data Science may be a good fit for you. The exciting part is that no matter how many months or years you had put in studying data science, 总会有新的算法出现, 技术和应用不断涌现. 这意味着你必须准备好永不停止学习. 在这个领域工作了2年，5年甚至10年. We see this as a positive; if you like challenges, keeping up with trends and get excited about data then you'll likely enjoy the roles that use Data Science. 持续学习意味着你将永远处于游戏的顶端.
A love of learning will also come in handy when it comes to extracting the data itself. 不像一般的软件开发, 你可以从哪里开始设计, implementing and testing as soon as you have a broad idea of what the requirements are, in a data science project you are hugely dependent on the availability of data. 的数据 可能 be t在这里, but the client 可能 also have legal or technological obstacles in sharing it with you. 另外, it 可能 be low quality or full of ambiguity and inconsistency or t在这里 可能 even be no annotated data at all. This may mean you have to learn and prepare months in advance by gathering and annotating data, 但这本身就能确保当你最终完成任务时, 你对它了如指掌.
2. 从一些特别的事情开始
Going into data science – just like any new discipline – can be overwhelming, 由于许多领域都属于“数据科学”的范畴，. 最大的问题总是“我应该从哪里开始??" Our advice is to approach a specific subject that is of the greatest interest to you, 或者是市场上最大的需求, 从这一点开始——这将帮助你保持动力. 例如, you may start with general statistics and machine learning to know the basics, 然后专注于自然语言处理, as t在这里 are currently many opportunities in the market for this type of role. 例如, 如果你从自然语言处理项目开始, 然后，您可以逐渐添加文档提取技能, 开发聊天机器人和推荐系统.
3. 有支持小组或导师吗
你可能已经在从事机器学习项目了, perhaps you're part of a team at a software company or you may have studied and researched Artificial Intelligence. Whichever walk of life you come from, be prepared for many people to question 你的 decision. 事实是, 学习数据科学可能很难, and t在这里 are many complicated mathematical and algorithmic concepts you will need to master, 但如果你有一个支持小组或导师, 这会让你更容易坚持下去. 俗话说:“共享问题减半”。, so consider having at least one person you can ask a question when you feel stuck. 从长远来看，你会发现这对你有帮助.
还有很多方法可以与数据科学家同行进行社交. We recommend joining meet-ups (you can now join remote ones from all around the world), 参加会议, 十大正规博彩网站评级脸谱网和LinkedIn群, 在推特和Quora上活跃. 也许最重要的是, we'd recommend finding at least one mentor - somebody that is already walking this path and can give you direction if you feel lost or you need a sounding board to talk through 你的 ideas.
4. 每个项目都很重要
You may have worked on many projects or connected with data science before, 这可能对你有利. We recommend that once you start doing educational data science projects, you treat every one of them as a way to help showcase 你的 work to the world. 我们这么说是因为它会! 与你在公司或为直接客户做的工作相反, 在大多数情况下, 教育项目 你的 知识产权及 你的 闪耀的机会. Putting effort into 你的 projects such as ensuring that the code is clean and everything is well-documented means you can later show these projects to potential clients and employers and be one step ahead of other applicants. 和, what is even more important is that new opportunities may come from people who saw 你的 portfolio or GitHub account and found skills and expertise that align with their project’s needs. 相信我们!
5. 要积极主动，尽快开始
The good news is that you're reading this - so that's already a good start. 许多人在数据科学教育上花费了数年时间, 写全球最大的博彩平台这门学科的论文，参加Kaggle比赛, 然而，他们并没有把自己的技能运用到数据科学的工作中. While having a solid general software engineering or other relevant experience can be a great plus, with years of waiting it is possible to lose the motivation to do the transition. So our advice is to start searching for jobs much before you are a qualified data scientist, maybe just a few educational projects 可能 be enough to land 你的 first job. 一开始可能会令人沮丧, 但你会在学习的过程中学习, and in months you may be far ahead of a person that spent their time waiting.
我们希望这篇文章有所帮助. 一开始，数据科学似乎是一个棘手的问题, 但是有了这些建议, 你很快就可以上路了. 如果你对数据科学方面的工作感兴趣，那就注册吧 hackajob. 只需要5分钟，公司就会联系到你!
就像你读过的或者想要更多这样的东西? 让我们知道! 电子邮件我们 在这里 或DM我们: 推特, LinkedIn, 脸谱网，我们很乐意听到你的消息.
