Lessons from a Senior Data Scientist
The aim of this article was for me to gain a deeper insight into the life of a senior data scientist and how their experience can be used as lessons for up-and-coming data scientists.
Photo by Kindel Media
As the data science industry continues to grow, I believe that it is important that people who are trying to enter the industry have a good sense of what they are getting themselves into. The aim of this article was for me to gain a deeper insight on the life of a senior Data Scientist and how their experience can be used as lessons for up and coming Data Scientists.
I would like to introduce Robin Cole…
Robin Cole is a Senior Data Scientist at Satellite Vu. He comes from a Physics background having studied at The University of Southampton where he then went onto doing a Master in Optics and Photonics at Imperial College London. A year later, he went to The University of Cambridge where he gained a PhD in Physics.
Source: Interviewees LinkedIn with Permission
Since then he has had various roles from Research Scientist, NHS Scientist Training Program, Optical Systems Engineer, Research Engineer, Data Engineer and now a Senior Data Scientist. He has skills in Data Analysis, Deep Learning, Data Engineering and Amazon Web Services (AWS).
With his strong educational background and variety of roles, I believe that Robin Cole can provide us with a greater insight of the technology and data sector.
This will be an interview style article. So let’s get started..
Questions & Answers
How did you get into data science?
I gained an undergraduate degree in Physics, in which I then went onto gain a PhD in Optical Physics. I then moved into the Research and Development field which consisted of programming. This is when I geared towards programming and went from working in labs and doing experiments to analyzing data.
I specifically used machine learning to tackle a lot of the problems where I was working in the Satellite sector and was using computer vision models. I used deep learning with images as part of my study.
What does data science mean to you?
There are a variety of roles in the data science field, and can be used in many ways. For example, in the ecommerce sector, you can use SQL and other traditional solutions such as Random Forests to help create a product recommendation engine.
In my role in particular, I focus more on deep learning and capture images on an airplane through computer vision. This deep learning approach allows me to process that imagery in order to identify and locate items of interests and classes.
My advice is that data science can mean different things to different people, therefore you need to explore the different areas and avenues of data science to see what interests you.
What do you do day to day?
My workflow imitates that of a software engineering approach in which we have two week sprints and daily stand ups.
I start my day at 9 and respond to my emails whilst checking for papers and blogs that are useful towards my research and to expand my knowledge. My daily stand up happens at 9.30am in which our medium sized team updates one another on the progress of their tasks. The rest of the day consists of the execution of solo tasks.
We have a bi-weekly catch up where we use this time to go into depth on what we are doing. We also use this time to manage our progress. Once a month, the team has a catch up where we focus on data science training needs and infrastructure such as AWS.
What are your plans for the future?
There are two routes Senior Data Scientists can typically go down: either they become more specialized in their field or they move onto a managerial role. For me in particular, if there are more Data Scientists hired in my team, I will possibly move onto becoming a Lead Data Scientist. I do not think too far ahead - as the business grows, my duties will naturally change.
I am currently in the early stages of working on remote sensing data, therefore a lot of general research is still required. So I will be focusing on that for now as that is my interest.
What is something that helped you get to where you are now?
Before becoming a Data Scientist, I spent a year doing Data Engineering which helped me to improve my programming skills, specifically Python. There is a lot of competition for data science roles and I realized how my year as a Data Engineer helped me in my data science career.
I was also the first person hired at the start-up I work at - so that meant I had multiple tech roles which allowed me to build skills, become more proficient and experienced.
What do you think new Data Scientists need to have?
Real world projects! As a Senior Data Scientists I get asked a lot of basic questions about projects which I believe is something that Data Scientists should know. When it comes to projects, a lot of online courses make you follow their guidelines which does not necessarily help you in the real world. I believe that Junior Data Scientists need to have the confidence to tackle projects by themselves.
Can you see the difference between University and Bootcamp Data Scientist?
There are obvious shortcomings in Data Scientists who lack traditional education, for example real world project management, how they approach the work and choose to present it. Again, the difference is that Bootcamp students lack real world project experience, which is very important.
What other advice would you give to up and coming Data Scientists?
When you see an opportunity - take it! My first ever machine learning project was when I wasn't even employed as a Data Scientist. I saw a small opportunity in which I could test, improve and show off my data science skills.
So my advice to up and coming Data Scientists is that if you see a small opportunity or area where you can show off your programming skills - do it! This provides you with real world experiences and makes you stand out from book smart students.
Another piece of advice I would give is to find a mentor. Working with a more experienced person will allow you to bounce ideas off them and get feedback on what you're doing. You can also use open source platforms, get involved in kaggle competitions, or act as a volunteer on a project as it will be a good experience.
I myself learnt and improved my skills through side passion projects where I used these real world projects to build my portfolio. These can also be used to discuss at an interview which can make you stand out!
Wrapping it Up
If you would like to know more about Robin Cole and his work, you can find and learn more about him here:
I would like to say a big thank you to Robin Cole for taking the time to sit with me to give us a deeper insight on what it’s like to be a Senior Data Scientist and what up and coming Data Scientists should do to better their careers.
Nisha Arya is a Data Scientist and Freelance Technical Writer. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.