Data scientists have become more prominent in the corporate world. Whether its translating SEO reports, carrying out complex financial algorithms or even helping football teams identify why they’re getting so many more injuries than their opponents.
More industries are showing their need for algorithms, data and analysis. This is a career that is only just getting started.
What is a data scientist?
A data scientist is someone who works with raw data and translates it into digestible, easy-to-understand metrics for others. Data scientists can work for businesses, charities or sports clubs.
Data scientists are often referred to as “data translators”. This is because a data scientist will often work with raw, often unfiltered data and need to “translate” the data into something more readable for the end user.
A data scientist or engineer will work with various sources and techniques. Some data scientists use algorithms, artificial intelligence, machine learning, statistical modelling or data mining to unearth the relevant data for a project.
A data scientist has a wide remit in terms of responsibility. Not all data engineer jobs will have the same responsibilities. These can vary depending on what industry you work in and what company or organisation you work for.
You will need an undergraduate degree for this role and a postgraduate one, depending on the industry you’re working in.
The most common responsibilities for a data scientist are:
- Assess each department’s need for data and how, if at all, it can be tailored for them.
- Build algorithms to supply tailored reports for each department.
- Conduct research and develop data gathering and translation techniques.
- Create reports that are easy to understand for the general reader.
- Liaise with members of other departments to gauge their data needs.
- Liaise with other data specialists.
- Research different statistical techniques.
- Test data effectiveness.
- Use machine learning and rolls.
- Working out what your company or organisation’s data needs are.
These responsibilities will change as you move through the role. If you move into management or more senior roles, you will be expected to manage a team of data scientists and negotiate budgets.
A data scientist salary will depend on the company you work for, its location and the industry you are working in. Your experience will also factor into your earning potential, as will your level of education. Salaries will start out low for a data scientist graduate, but will grow with experience.
To begin with, generally, a junior data scientist, junior data engineer or starting data engineer salary will start between £25,000 and £35,000. This can rise as you gain more experience in the role, however.
Once you have enough experience and a senior enough job title, you can expect to earn between £40,000 and £60,000. Those who are chief data scientists or data leads can earn as much as £130,000.
You will need an undergraduate degree for this role and a postgraduate one, depending on the industry you’re working in. You may also want to specialise in niche or specific areas by combining a different subject, such as a business studies degree with more data-led qualifications at postgraduate level.
The best subjects to study at university for a data scientist are:
- Computer science degrees
- Data analytics degrees
- Data science degrees
- Engineering degrees
- Finance degrees
- Mathematics degrees
- Operational research degrees
- Physics degrees
- Statistics degrees
- Sports science degrees
It is best to know which industry you want to work in before selecting your degree. Those working in business or corporate settings may need to have experience in programming and computer analysis, whilst those in sport will need to have a more mathematical approach.
If you decide to study at a postgraduate level, you can focus on more specific courses related to data. These courses will take a more focused view of data analysis and will teach you niche skills and abilities beyond simple analysis.
The best subjects to study at a postgraduate level are:
Some of these subjects are only available when studying a master’s degree or a PhD. The work involved in these courses and may need you to complete some form of work experience or placement beforehand.
Training and development
The company you work for will likely have your training and development handled in-house. Despite this, you will also be responsible for your own training and development and keeping up-to-date with industry changes.
Work experience isn’t too difficult to come by, but it will largely depend on the area you are applying in.
The training you do will not necessarily be entirely data-based. You may be required to take on specific industry training courses. For instance, those working in sport, may be required to train in specific areas of that sport, to enhance their learning.
There are still some institutions and companies that will offer data-specific courses. Institutions such as The Royal Statistical Society (RSS), BCS, The Chartered Institute for IT or the Office for National Statistics (ONS) offer a wide variety of training courses and professional development platforms for registered members.
As data analysis is quite a niche and specific topic, more focused training courses will fall under your remit. You will be expected to learn new skills, liaise with industry professionals and attend networking events to expand your skill set.
For those working in modern sport, you may be expected to expand your knowledge with other training courses. For instance, those studying as a data analyst, football data scientist or sports scientist at a football club, may be expected to complete their coaching badges with the Football Association. These will enhance your knowledge of the sport and allow you to provide more detailed assistance to your colleagues.
Data scientists need a variety of different skills in order to be successful. These skills can be further honed through advanced training and development.
The skills needed to become a data scientist are:
- An ability to communicate and present data in an easy-to-read manner.
- An ability to work under pressure.
- Brilliant problem-solving skills.
- Excellent analytical skills.
- Excellent organisational skills.
- Good attention to detail.
- Time management skills.
As you move into management or more senior roles, you will need more specific skills related to team leading. At this level, you will need to have the ability to manage and encourage your team, manage workloads and have an ability to collaborate with other department heads.
Work experience isn’t too difficult to come by, but it will largely depend on the area you are applying in. For instance, shadowing an analyst as they run analytical models of a company’s SEO potential will have minimal pushback compared to wanting to shadow someone who is in charge of personal medical data.
Placements or a data science internship at university are a good way to gain experience too. Not all companies will have internship placements, but if your university has good connections with local businesses, you may be able to take on a short placement.
Registering with institutions such as the RSS, BCS or the ONS can be helpful too. These institutions will have placement opportunities and vacancies listed there and useful classes to help you find work. Websites such as Kaggle and Topcoder are good for a graduate data scientist and for ways to find data science jobs.
Your ability to progress in your role will largely depend on your industry. For instance, those working in the NHS or in a government department, will have a more defined career path, particularly in the NHS, who have their own Agenda for Change (AfC) pay scales, which will also dictate your own progression within that industry.
A data scientist is someone who works with raw data and translates it into digestible, easy-to-understand metrics for others.
Those working in sport, may have a less structured approach to progression, but with more support to get there. Sports science and data analysis are becoming huge parts of how cricket, football and rugby are all monitored, even one-man sports like golf have a need for data scientists to aid their game. It is possible to oversee teams of scientists and analysts within a specific team or institution. You may find senior roles and progression easier, even if the progression isn’t as defned. Sports clubs rely on their head of data science to make a difference for them.
The skills you acquire can also be used across a range of other industries. Some data scientists may decide to move into teaching, tutoring or freelance consultancy work, all of which can be highly lucrative career paths.