How I Became a Data Scientist
Six months ago, I decided to change my career from science to data science. Today I signed my contract for a data science position. Here’s how I did it.
After finishing my undergraduate degree, I realised I loved research and wanted to continue it further. My dissertation was on UK mosquitoes and the entomology subjects fascinated me, which resulted in me signing up for a Masters in Entomology. The research project involved three months fieldwork in Borneo collecting mosquitoes and my supervisor managed to find funding for a PhD. The project was interesting and I decided to continue along the academia pathway. I assumed that I would eventually become a lecturer.
During my PhD, the project had highs and lows. Despite spending an amazing year and a half in the rainforest, my mental health was deteriorating. My imposter syndrome was at an all-time high and I couldn’t seem to overcome it. I decided during my final year that I did not want to continue in academia. My husband mentioned data science at this point, but I still wanted to give biology research a try (it’s what my background was in!) and I applied for jobs in industry. I was offered a job at a small company working on formulating pesticides. The team were helpful, supportive and knowledgeable, and I learned a lot within that time. Due to the size of the company, it was not possible to progress and the daily commute was difficult. This ended with me changing jobs and working as a laboratory manager at a research institute. I chose this career path because I wanted to increase my management experience.
“I missed problem solving, data analysis and R”
After a few months of maintaining the laboratories, I realised that the job was not for me. I missed problem solving, data analysis and R. I knew I didn’t want to be in the laboratory forever, but I was unsure about which direction to go. I met up with my previous PhD lab group and one graduate had converted into data science and told me about his experience. I tried to find out more about the career path and decided to go to my first data science meet up (Inspiring Women in Data Science). I was still conscious that most data scientists had a strong mathematical background and this worried me, so I considered extra training.
I researched masters, bootcamps and online courses and weighed up the pros and cons of each. I decided to go for Cambridge Spark because I could continue working and I liked sound of the course material. I almost signed up for the virtual course but I work better in a classroom environment and knew I would get more from the course by attending in person. The course used python and I was convinced I would struggle due to only knowing R. Olivia from Cambridge Spark reassured me and with only three weeks left until the first weekend started, I worked through their pre-course material and learned python.
The first weekend was intense and many subjects were covered. Git and conda were a struggle and the teachers were there to help. The first weekend made me think that the subject was too difficult for me but I spent the two weeks between study weekends trying to catch up. As the weekends went on, I saw a massive improvement in my python skills and knowledge. The extra work was paying off and I no longer behind during the hands-on sessions. The more work I put into it, the stronger my confidence grew.
I complemented the course with:
- Meetups (IWDS, R Ladies, PyData, London Data Science Workshop, IBM AI, Toyota connected tech nights, Learn Machine Learning)
- HackerRank problems
- Analysing Kaggle data (e.g. Lego data on my GitHub)
- Reading blog posts
- Working through O’Reilly books (‘Data Science from Scratch’, ‘R for Data Science’)
- Datacamp (Data Scientist track) during my lunch breaks.
After Christmas, I decided it was time to focus on applying for jobs. I had applied to a few junior roles, but hadn’t heard from any of them. This was a sign that my CV was not good enough. IWDS ran a CV clinic in November and made changes based on their advice. I also asked my data scientist friends to read through my CV in return for drinks. I could have waited until the end of my course until I had all the relevant skills, but I was told that women generally only apply for jobs once they have a high number skills listed on the job advert. I wanted to change this habit.
“I asked my data scientist friends to read through my CV in return for drinks”
After the changes, I received phone calls from recruiters and managed to get my first interview in January. I was not as confident as I should have been and I didn’t show how much I learned during the course. Practise makes perfect. I learned from my mistakes and I ended up getting a job offer and will be starting in April.
My advice from the job interviews:
- Practice project examples (ideally data science projects)
- Know your CV
- Know who is interviewing you
- It’s OK to say you don’t know
- Be confident!
I don’t know where my career will go from here but I do know that I enjoy learning, looking at data and programming. Careers don’t have to be a straight line and it’s OK to change direction whilst finding out what you enjoy.
The advice I would give when changing into data science:
- Network as much as possible
- Practice data science skills
- Present your work
- Do tutorials but take it further. Find data, analyse it and put your work on GitHub
- Attend hackathons- it may result in jobs
- Keep learning & believe in yourself!
Things to avoid:
- Don’t overdo the complicated subjects before learning the basic ones. I went to a few Meetups with presentations on subjects I had no idea about and I tried to join a more complicated Kaggle group at a Meetup. It resulted in me feeling like I didn’t know anything. It’s good to introduce yourself to new subjects, but don’t get overwhelmed
- Don’t start too many projects without completing others
List of resources
I would list a variety of resources, but another Cambridge Spark alumni has already provided an extensive list of resources on his blog: https://medium.com/@FreddieO/how-to-become-a-data-scientist-in-12-months-7e0deb51fac5
Other resources I found useful:
- Shirin’s playground
- Advent of code
