So, you want to work in Data Science?
Data Science is a discipline that incorporates the application of statistics, data analysis, machine learning and computer science. The goal? To get value from data through analysis so as to better understand how a business is performing. With this information, the Data Scientist builds AI tools to automate certain processes within the organisation.
There are a number of tools at the Data Scientist’s disposal, though candidates are not expected to be an expert at everything, but a depth of expertise in a specialist area is critical. You cannot simply skim the theoretical surface, you must be able to apply it in practice.
The job title of Data Scientist suffers from a lack of definition and typically finds itself being used as a one size fits all label when it comes to related jobs in the field. Case in point, Data Analyst is often wrongly assumed to be synonymous with Data Scientist, and while it shares some similarities in terms of skills and responsibilities, those working in data analysis cannot simply hop into a data science role without additional learning and experience. So, a note to candidates, while it may sound obvious, read the job description carefully before applying for Data Scientist jobs to ensure that you are fully qualified and have the experience and skills required.
Data Engineer, Machine Learning Engineer, Data Science Generalist, Software Engineer and AI Hardware Specialist all fall under the umbrella of data science jobs you can look out for along with the obvious, Data Scientist.
Individuals with a strong grasp of both data analytics and business metrics or those for whom coding is second nature are the candidates organisations are looking for to fill those roles. You need to have the likes of R and Python in your back pocket because data science jobs are largely driven by programmers who are skilled in coding, building data models, extracting insights from data and problem solving.
Employers are looking for individuals with an average of 3-5 years industry experience, in some cases who have studied to master’s or PhD level in subjects including maths, statistics, computer science or a similar quantitative field. You should be able to demonstrate experience of working with data sets, building statistical models and data visualisation tools.
A good grasp of SQL and ACL is key in aiding your competency with retrieving data from databases, but just as effectively as you use your technical abilities to probe into systems like MySQL, Oracle and DB2, your communication skills should be just as sharp and strategic. Harbouring a deep understanding of both the application of data science and the very core of the business itself, you must be able to relate one to the other. You will need to be able to properly convey the significance of your findings to the business, and when it comes to stakeholders who are stuck in the traditional ways of the pre-tech era you must engage your powers of persuasion to unearth their challenges, translate them into data-driven issues and communicate how you propose to overcome them within the data science framework.
The ideal data science candidate wields excellent critical thinking skills, proactive problem-solving skills, intellectual curiosity, business sense and the gift of the gab! Pair this with the technical skillset to write efficient and sustainable code, leverage machine learning and AI as well as self-service analytics platforms and manipulate maths and statistics to their whim; you need the depth of expertise in these areas to stand out.
With plenty of free courses available online, if you want to pursue a career in data science then the theoretical aspect is easily attainable. Where the hard work comes in is at field level. Employers want to see hands-on experience you can attest to. Whether it’s projects you’ve been working on at home, or within your previous or current workplace, use all those opportunities to build a working portfolio. Experience is key in data science jobs, something you’ll be short on if your background is not in a quantitative space.
Use free platforms such as Tableau Public to publish interactive data visualisations from the projects you’re working on and only undertake the projects that will qualify you for the data science jobs you’re best suited to.
The salary range for data scientist jobs in the UK can start around £35,000 and build to upwards of £150,000 for the more senior roles. The average UK salary sits somewhere between $60-80,000. While in the US, the average salary for a data scientist comes in around $122,240.