As job markets worldwide have become more competitive and applicant selection criteria have become more opaque, and different (and sometimes contradictory) information and advice is available for job seekers wishing to progress in their careers, it has never been more difficult to determine which factors in a r\'esum\'e most effectively help career progression. In this work we present a novel, large scale dataset of over half a million r\'esum\'es with preliminary analysis to begin to answer empirically which factors help or hurt people wishing to transition to more senior roles as they progress in their career. We find that previous experience forms the most important factor, outweighing other aspects of human capital, and find which language factors in a r\'esum\'e have significant effects. This lays the groundwork for future inquiry in career trajectories using large scale data analysis and natural language processing techniques.

翻译：随着世界范围内的就业市场更具竞争力,申请人甄选标准变得更加不透明,而且希望事业进步的求职者可以获得不同的(有时是相互矛盾的)信息和咨询,确定哪些因素对职业进步最为有效。在这项工作中,我们提出了一个新型的大型数据集,涉及50万卢比以上,并进行初步分析,以开始对哪些因素帮助或伤害了希望在其职业生涯进步过程中向更高级角色过渡的人。我们发现,以往的经验构成最重要的因素,超过人力资本的其他方面,并发现r\'essum'e中的哪些语言因素具有显著影响。这为今后利用大规模数据分析和自然语言处理技术对职业轨迹进行调查打下了基础。