A Day in the Life of a Data Scientist: Expert vs. Beginner - KDnuggets

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With more people entering the tech industry, it is good to get an understanding of what you day-to-day looks like. I have kindly asked Jose Navarro and Andrzej Ko?czyk to give us a breakdown of what their days look like with the aim to help others prepare themselves.

The two are in different stages of their data science career, helping people from both scopes. Not only will you understand what an expert Data Scientist gets up to, but for those who are new to the industry - you will also get an understanding of what a beginner Data Scientist is doing to become an expert

So let’s learn more about what a Data Scientist gets up to.

First we have Jose Navarro, a Data Scientist working at Qbiz. This is what he had to say:

I consider myself very fortunate to work as a data scientist. I think it’s a job like no other, that allows us to solve complex industry problems with the help of statistics, powered by computer science. I will describe here how my day-to-day life looks, so you can get a better image of it.

I work from home some days, and some others from the office, as I think face to face interaction with the co-workers and the rest of the team is important for the development of both projects and careers.

It is a very flexible job, and it normally allows me to accommodate my personal life around the needs of the project. If a good work-life balance is essential for you as it is for me, a career in data science is not a bad option.

If I’m working from home, I usually switch on my laptop at 9 am, after a quick school run with my daughters. Then there will be between one and two hours of meetings. Meetings are crucial for the project, and good communication is key to understanding what the industry problem is, what is expected from each member of the team, how to achieve the solution, or what the results are. A data scientist should be able to use their soft skills to communicate effectively and to present to all types of stakeholders of a project, tailoring the language to the audience in each case.

The following part of the day is related to the hard skills of this job, applying technologies like Python, SQL, etc. Depending on the stage of the project this part can vary a lot, from brainstorming to data visualisation, including data collection, data cleaning, labelling, statistical modelling, parameters tuning, etc.

Around 1 pm I stop and have lunch for 30-60 min. I make sure to stretch my legs and to look far away to rest my eyes. There is no reason a data scientist couldn’t follow some healthy habits. Health and fitness will help us with our hormone levels, with some work-related benefits as well, like increasing our creativity and capacity to focus.

I finish the day around 6 pm, making sure I have some time left for learning. I check the latest trends and state-of-the-art techniques with the help of pages like KDNuggets and services like Kaggle, Twitter, LinkedIn, or Medium. One of the best things of being a data scientist is that learning is always encouraged. With an ever-changing environment around Data, machine learning and artificial intelligence, keeping up to date really pays off (on top of how exciting this world is).

No two days are the same, and there are always new things to try and new problems to solve. Let’s build the data driven future.

The next person that will give us more into their day to day life is Andrzej Ko?czyk, a Data Analyst inspiring to become a Data Scientist

At the beginning I would like to briefly introduce myself. Currently I am working as a Data Analyst and till November 2021 I did not have any knowledge related to data science/ Data Analysis / Data Engineering. I've graduated from a totally different study, but I have always been data enthusiastic. Due to that in November 2021 I've started data science Bootcamp and have started to learn using additional online courses, tutorials. During my bootcamp course I've learned much about SQL, Tableau and Python libraries, which help me now understand and grow up as a new member of the data science family. 

That field is now for me so interesting, as I've started to build my own ML models based on real data ! I think that data science is really the future and you can have some great time when you are still learning. In my opinion it is not the easiest field - sometimes you have to spend many hours understanding a problem and develop your ideas - but that is really fascinating. When you finally  have some results, maybe not the best in the beginning - but you know that you did it. That is exciting. 

As I've mentioned - I am still a beginner, but I would like to learn more and change my position soon from Data Analyst to Data Scientist. What do I need to achieve that? I think that will be good tips for everyone, who would like to roll into our family: never give up, learn, read and finally keep progressing by making your own projects. That is the most important part. During model creation you can always find out something new. Other things like tools such as Tableau, SQL, etc are also important, but you will use them when you will make projects as well :) 

To summarise: for me data science is an opportunity which is fun and exciting and really has an effect on business in our world :)

I hope this gave you a better overview of what the two levels of Data Scientists get up to, taking on their responsibility, advice and more.

    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.