Eight tips to consider when changing career and moving into data science

Are you having a career break, thinking about a career change, or considering moving into a data science or data position? I’ve worked in many roles in the data and computing sectors over the years and wanted to share some tips and ideas about how to keep learning while maintaining a work-life balance. If you’re considering moving into a new field or looking at career options after taking some time out, here are some learnings from my own journey that might help you on your way.

1) Put time in your diary for learning

In many people’s lives everything is urgent, and you end up constantly busy. While we all know learning is important, we rarely prioritise it. In the Data Science field particularly, it’s vital to keep up to date with the latest developments. So, try to prioritise this by reserving time in your diary.

There are many helpful resources available to help you develop your digital skills for free:

• Microsoft’s digital skills site is a good place to start as it has lots of resources for different roles
• Code Academy is a wonderful site where you can learn to code
• Microsoft’s Professional Program has vocational courses on everything from Data Science, the internet of things, AI, data analysis and entry level development
• AI School contains videos and articles suitable for beginners and experienced people alike

2) Take career coaching

I undertook coaching when I was at a point in my career where I was successful yet keen to try something new. I wanted more meaning and enjoyment in my work. There are books that can take you through similar approaches, but I also recommend being coached by a professional. It helped me identify my values, strengths, achievements, passions, interests and skills. By better aligning my life with my values both inside and outside work, I realised I could find both more rewarding. I discovered what was important to me and that I wanted to do something innovative that made more of a difference to others, and involved working with a wider variety of organisations and people.

I decided to undertake an MSc in Smart Cities and Urban Analytics at UCL. Since then, my career has taken on an exciting new path. I’ve worked with many different organisations, including start-ups, universities, cities and academia, on initiatives that aim to improve people’s wellbeing, the environment, urban services and economic development.

In my current role at Microsoft, I’m lucky that the company’s culture aligns well with my values. For example, Microsoft is committed to advancing diversity and inclusion within the technology sector, helping to drive higher proportions of women and minority groups to pursue careers in this area. Through this, I was able to help with a DigiGirlz event to teach 12 year olds how to code.

3) Learn skills in growth areas that interest you

Understand the direction that’s right for you. Then, by studying or working in a growth area where you can push yourself outside your comfort zone and develop new skills, you’ll have access to more opportunities.

I chose to do an object-orientated project during my first degree, which proved to be invaluable in my early career.

In my previous job I was given the opportunity to specialise in analytics. Learning skills in growth areas allowed me to move in new directions and get the job I have today at Microsoft. Data Science is one of those growth areas, so it is well worth considering.

4) Take on a new role using existing skills

Moving into a new role where you already have some strong skills makes the transition easier. When I went into training, I already had a lot of experience running workshops, as well as real-world experience in the software design and architecture that I was teaching. This was invaluable, and although teaching was new to me, I had many transferable skills.

Be open-minded about recognising your transferable skills, as so many people take their skills for granted.

5) Consider part-time/flexible working

After taking maternity leave, I initially went back to work for three days a week, before increasing that to four days a week. My husband started to work four days a week as well. This meant our daughter could spend a day a week being looked after by each of her parents. Working part-time, I continued to progress in my career and was promoted to a senior level as well as still being able to work from home sometimes.

When my daughter was at school, working four days a week also enabled me to study part-time for an MSc at The Centre for Advanced Spatial Analytics (CASA) at UCL. The teaching staff contained several world-class experts, so I found my studies really inspiring. I was very lucky to have been taught quantitative methods by the gifted mathematician Dr Hannah Fry, who also educates the nation via the BBC on complexity, data, Ada Lovelace and more.

Of course, working and studying at the same time is difficult, and is not something I could have done when my daughter was very young. I had a lot of support from my family and friends that made this possible. For me, making time for family is essential and I make sure I can attend important events such as Christmas plays and parents’ evenings.

6) Share your skills and expertise with others

Sharing knowledge with others is great. Not only do you have an incentive to learn – to share with your friends – but by explaining and listening to others and discussing ideas you expand your own understanding, too. It makes learning more sociable and fun. So, find a learning group, attend meet-ups, or create your own. I’ve found this has accelerated my learning.

You can also share ideas through writing, such as blogging, social media and creating tutorials. These are all healthy ways to learn, develop skills and engage with a wider community. Writing not only helps you clarify your own thinking but can also have a very broad reach. Powerful points of view tend to emerge when you have deep expertise in an area, but can also have an impact when you take an existing concept and relate it to another domain. In my career, I have written about Lean and how that relates to DevOps within software development. Putting these ideas together was a new concept and it created an influential piece of work. DevOps is also very important in the world of data.

7) Connect with the big picture

Finding out who the experts are in your area of interest and reading their work, following them on social media and listening to their talks can be very helpful, as can finding organisations and people that inspire you. In Data Science, the Alan Turing Institute hosts talks around the country that are worth attending. I also love NESTA, which conducts excellent policy research, and the Royal Society, which always has lots of interesting things to say about data and AI.

Taking time to look at a wide range of viewpoints can be beneficial, giving you a more rounded and inspired perspective.

8) Adopt a growth mindset

I first came across Carol Dweck’s book on growth mindset during an evening talk at my daughter’s school. I would highly recommend reading it, if you haven’t already. The idea is to embrace challenge, listen to feedback and take inspiration from others in order to improve learning and resilience.

At Microsoft, growth mindset is a core part of our culture. I have found this very refreshing. In the six months I’ve worked here, I‘ve learnt an incredible amount and I can’t wait to continue learning much more.

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Considering a career in data science?

Take a look at some of the resources available to help you develop the necessary skills you need to succeed in Data Science – from workshops to online courses that help you make the most of your LinkedIn profile.

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About the author

Paula works in Microsoft’s Customer Success Unit, helping customers use analytics and AI on Azure to their full extent for maximum ROI. Her background is in software architecture, analytics and software development. During her career, Paula has enabled enterprises of all sizes to become more data-driven.