App Annie 是全球最大的移动应用战略决策平台,为开发商与发行商提供开发、销售和投资应用需要了解的全部信息。超过 80 万应用使用 App Annie 追踪其表现,超过 40 万移动应用专业人士(包括 94%的 100 强发行商)依赖 App Annie 帮助其做出明智的商业决策,这些企业包括 Electronic Arts 、 Google 、 LinkedIn 、 LINE 、微软、耐克森 (Nexon)、雀巢、三星、腾讯、 Bandai Namco 、环球影业 (Universal Studios) 和道琼斯 (Dow Jones)。 App Annie 是一家私有的跨国公司,总部位于美国旧金山,在阿姆斯特丹、北京、伦敦、纽约、首尔和东京等全球 12 个城市设有办公室。公司已从 e.Ventures 、 Greycroft Partners 、 IDG Capital Partners 、 Institutional Venture Partners 和 Sequoia Capital 筹集到了 9400 万美元的融资。
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岗位职责:
We ’ re looking for an experienced developer who can lead teams and create innovative new products in the analytics and data space. You will lead the development team that creates the world's #1 Apple App Store analytics service. Together with the team you will build out new product features and applications using agile methodologies and open source technologies. You will work directly with the Director of Product and Director of Engineering, and will be on the front lines of coding new and exciting mobile app analytics products. You should be passionate about what you do and excited to join an entrepreneurial start--up.
You should be a strong engineer with significant experience in back--end system design, profiling and optimization (database / software design). You ’ ve worked at companies before at a management level and therefore know what it takes to lead, manage, mentor and train.
5+ years computer development experience, or less experience if exceptional skills combined with a Computer Science degree
Good communication skills with management experience
Great mentor to junior and mid level engineers
Passionate about and good understanding of development methodologies such as XP, Scrum and RUP
Good working knowledge of at least 2 of the following topics:
Programming languages: Python (preferred) or C#, Java, PHP, Ruby
Browser technologies: HTML/CSS/Javascript/jQuery
DB development: PostgreSQL or other server database
High performance computing: in--memory database, cloud computing, caching optimization techniques, cluster management, etc
Data mining: statistics and data visualization (R, SPSS, SAS, Matlab, Mathematica, pandas, Tableau), analytics databases (Vertica, Sybase IQ, etc.)