For those who are interested in data science, you will quickly come across individuals providing tips on how to acheive a job in this remit.

However, after some time attempting to emulate it, to my dismay I found some concerning aspects.

Résumé

One key aspect is how a CV should be written. In the majority of cases, individuals will say, One side of a A4 page. However, as sources highlight, what is regarded as A4, one side of a page can vary between jurisdictions.

Likewise, resume writting in different countries differ, In the UK, it is typically two sides of A4 (Prospectus, 2021) and in countries such as Japan, photoes are expected to be included.

These variations are rarely fully ackhnowledged and/or alternative resources are provided for such inviduals.

Application process

Another aspect that has made me concerned is the discourse around the application proccess itself. In the US, from what I can gather it is very much centred around the CV. However, in the UK, I have found a growing number of companies opting to use a standard application form. A standardised process enabling recruters to shift through applicatents easily.

This variation in the two applications has major implications. In the UK, where such applications are used, adding non-university qualification can be extremely difficult. Often the providers of such services do not appear to be well versed in UK qualifications such as A-levels, making it hard to desipher how they should be classified. Likewise, if you have done courses from Coursera or Edx, regardless of whether the material has been provided from an university, there is no clear way of including them. They arent a degree or a micro-degree. Where do they fit in?

A similar fate awaits the projects that asspiring data scientist do to circumvent the lack of direct experience. In a CV, you have the flexibility of including them. In a form, you must abide by the categorties provided and there is no projects.

Further implications

There are two major implications of this.

Firstly, belief in self study leads to indviduals looking down upon those who have chosen an academic route. Now, there is no denying that formal university educations has its limitaions, including current industry standards and costs. However, they do have some values such as circumventing the blocks related to the form based application systems. A degree especially in data science will cover you when you need to show your skills in the sector (I'd hope).

Secondly, there is a risk that you are selling a dream that may not be realistic to many. As globalisation brings us closer, we must be ever more acutely aware of the distinctions between nations and what it entails. Data Scinece is strengthend by diversity but it must be applicable to the full remit of it.

Conclusion

Where does this leave me?

I hope one day to establish a career in data science. However, I also find learning and working on data science extremely rewarding regardless. I am also acutely aware of the importance of having a robust knowledge of the field, after experiencing how a computer vision mistakenly categoried me as an Indian, presumerably due to the lack of tranining dataset of South Asians in the dataset. As such, I am keen to undertake a masters in AI in 2023.

Wish me luck!