How to become a freelance data scientist

If you enjoy analytical thinking, and using technology and tools to interpret data, then find out how to become a freelance data scientist. It’s a consistently growing and in-demand speciality, as an increasing number of businesses look to turn numbers and large datasets into business insights.

From new technology start-ups to governments, organisations can collect more information about people than ever before. But there’s a huge gap between having access to that data, and turning it into actionable insights, whether it’s to attract new customers, help employees to be more productive, or changing the habits of an entire population.

That’s where data scientists come in. You’ll be solving the problems faced by businesses and organisations, using the latest tools including data mining, artificial intelligence and machine learning. And the value of those insights can make for an extremely well-paid freelance career.

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Why become a freelance data scientist?

The idea that people should be pigeon-holed into either being solely creative or analytical has largely disappeared, and the growth of data science is one reason for that positive change. Compared to the traditional role of a statistician, data science allows much more scope for identify issues and potential sources of information, and developing new tools and software models to collect everything required to create solutions.

If you enjoy maths, analysis, and using new technology, then it’s certainly a field worth exploring, particularly if you want to see your insights used for practical changes in the real world.

But on top of those areas, it also offers the opportunity to collaborate with wider teams and present directly to the management and leaders of the organisations you work with. Turning your insights into compelling stories will help them to be accepted. And developing new data models or ways to use data mining and artificial intelligence (AI) will engage your creative side, along with creating and programming tools as needed.

Becoming a self-employed data scientist lets you have more control over your career. You’re able to focus on the areas and specialisations which interest you the most, whether that’s a particular industry sector, or highly-skilled tasks.

It also offers more freedom and flexibility to suit your personality and lifestyle. You don’t need to be located in an office to access a powerful computer and high-speed broadband. And you may want to work part-time, or around other commitments, whether that’s to take care of your family, or your physical and mental wellbeing. Or working from home may just be preferable, allowing you to set up your home office and environment to let you be more productive without the hassle of commuting and office politics.

And working across different clients can give you access to a wider range of data and insights, or let you apply models and techniques from one sector to different types of businesses or organisations.

 

What do data scientists actually do?

Both data analysts and scientists are expected to find patterns or trends in data which can show organisations how they can make improvements. But data scientists are expected to identify the issues which can potentially be tackled. And then set out how that information will be collected and interpreted.

This means designing experiments, building algorithms, selecting data mining models, and then using machine learning and AI, assessing how effectively it’s working along the way. This includes using languages and tools including Python, SQL, SAS, R and Hadoop.

What do data scientists actually do?

When the data has been collected, analysed and interpreted, you’ll then be expected to translate the information into insights and actions which an organisation can follow to produce change. Whether that’s altering the buying habits of online shoppers, encouraging patients to take better care of their health through an app, or recommending future scientific research.

You’ll also need to be curious and enthusiastic about testing the latest technology and techniques, and developing prototypes and proof of concepts to test your ideas and suggestions.

 

What skills, qualifications or experience do you need?

It’s possible to become a freelance data scientist without any formal qualifications or experience, particularly in a time of high-demand. But if you’re self-taught, you’ll need to work hard to demonstrate your skills in order for clients to potentially trust you with business-changing decisions.

Most data scientists will typically have a degree in relevant fields including computer science, data science, engineering, maths, physics or statistics. And many will have gone on to postgraduate study for a Masters or PhD, with subjects including big data, business or data analytics, data science, machine learning or AI. Some employers do offer apprenticeships, including The Defence Science and Technology Laboratory (Dstl) or training providers like Cambridge Spark.

You’ll need to have some programming skills in languages including R, Python, SQL, C or Java, and have good database design and coding abilities with tools such as SQL and MySQL. And how to clean, manipulate and organise data (known as data wrangling), along with the concepts of machine learning. Along with a working knowledge of the big data tools commonly used, including Apache Spark, Hadoop, Talend or Tableau.

How to become a data scientist - skills and qualifications

That might seem like an immense amount to learn, but you can tackle one area at a time to build up your knowledge. Many free or open-source tools not only allow you to start using them for free, but also have libraries of existing code and solutions available, which allows you to learn from the work of others as well as saving you time in the future. There are also lots of online communities for data scientists for advice and tips from those with more experience, from social media groups to formal set-ups including Data Science StackExchange or Kaggle.

Ultimately, you’ll need to develop a range of skills including:

  • Analytical and problem-solving skills
  • Excellent attention to detail
  • Creativity and resilience to develop ideas, and motivate yourself if your first attempt fails
  • Database coding, interrogation and analysis
  • Programming
  • Machine Learning and AI
  • Communication and presentation skills
  • Organisation, time and project management.
  • The ability to collaborate effectively
  • Constant curiosity and pursuit of new ideas and learning

Due to the popularity and demand of data science, there are a huge number of online courses available. Before paying for any training, it’s important to check the provider, details, and whether it’s accredited by a recognised organisation.

For example, the SAS Academy for Data Science, or credentials and certification offered by the likes of Amazon and Microsoft. A variety of online courses are accredited and recognised by leading universities or organisations, and can potentially be used as credits towards a degree, for example, the IBM Data Science Professional Certificate, which is recognised by the University of London. If you’re not sure about pursuing data science qualifications or choosing it as a career, why not try some of the free courses offered in data science by services such as Coursera to see whether it suits you.

 

How much can a freelance data scientist earn?

Any self-employed income can vary a lot depending on factors including your skills and experience, the demand for your services, and how well you can negotiate with clients. So, any figures quoted are to give an idea of the potential in a particular sector.

Becoming a freelance data scientist could be a lucrative career move. The average UK salary for data science jobs is estimated at £67,500 (Totaljobs), and in London, at £75,568 (Reed). And as a freelancer in the UK, at £77,000 (Glassdoor). If you choose to work for an employer to build your experience, entry-level wages begin around £25,000 to £30,000. But an income of above £100,000 per year is not uncommon for lead and chief data scientists, including the self-employed.

Securing the highest freelancing rates as a data scientist means working with large tech companies and leading organisations, so you’ll need the skills and experience to attract those clients. Remote working has become much more widely accepted, but it’s still helpful to be located in an area of high demand, whether that’s London, or other tech cities and hubs including Cambridge, Manchester, Bristol, Birmingham, Leeds, Edinburgh or Belfast.

 

Finding work as a freelance data scientist

As you become an established freelance data scientist, it should become easier to maintain a regular flow of client enquiries, although with any self-employed career there will be times when demand for your services goes up and down.

Networking with other freelancers, joining online or real-world data and tech communities, and referrals from previous clients will all help in finding suitable projects.

But if you’re just starting out or struggling to find enough clients, there are a range of resources online including the dedicated DataScientistJobs site, and more general technology sites including CWjobs and technojobs, along with opportunities offered on LinkedIn or Twitter.

You can also develop your skills and earn by taking on more junior gig work, including data visualisation or data cleaning. These tasks can be advertised on specialist or general freelance job boards, or you may find more experienced data scientists are looking for help and support, which can also lead to coaching, mentorship or work referrals as you develop your skills and build your relationship with them.

 

More resources and support to become a freelance data scientist

Researching other freelance careers? Why not check out our other guides:

And you can get support and help if you’re starting out with self-employment, or still in the early stages of building your career, with the IPSE Incubator. The 12-month programme is currently free with IPSE membership, and includes advice, events, webinars, networking and more, tailored to anyone just beginning their freelance business.