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How An Unemployed Data Scientist Structures Their Day

Keeping Order Is Important

Getting Started

Photo by Halacious on Unsplash
Photo by Halacious on Unsplash

Introduction

Let’s start by stating the obvious… There is a pandemic going on and it is affecting the market.

I’ve seen tons of "Open To Work" pictures on LinkedIn (including myself), talk less of the bold people that create a post sharing their story of how they were laid off with a nice resume attached – honestly, I commend them all for their boldness. And we can’t forget the recent graduates who are now keen to begin their professional careers.

It has been tough!

Technically, I am still employed until the 16th of this month though realistically I’ve been furloughed since March. Needless to say, I’ve needed to set a standard for myself to ensure I am doing things to develop myself as a Data Scientist from a career standpoint— You can read more about what specifics I have done to ensure this is the case in "How I leveled up My Data Science Skills in 8 Months".

How I Levelled Up My Data Science Skills In 8 Months

The first thing that became apparent to me when I was first furloughed is I need order. I am one of those people that need to have some sort of structure for my days with a clear idea of what I want to accomplish for that day – No, I am not talking about a to-do list. I feel if I don’t have structure, my day goes out the window and I start feeling guilty at the end of the day at the lack of accomplishment, which can easily spiral into a cycle of self-doubt.

With that being said, I thought it necessary to share how I currently structure my days to serve as a form of thought provocation to other Data Scientists that are currently out of work for whatever reason.


The Routine

My Handmade timetable
My Handmade timetable

Above is a real image of the timetable which I created and strategically placed above the TV in my room. Of course, it’s not rigid, but I follow it as closely as possible with a few amendments.

5.05–5.25: Mindfulness; 5.45–6.30: Exercise

Note: Discussing these two together since they are as important as one another

We all know the strain of job seeking in the Data Science arena. It’s tiring. That’s not even including all the rejection you will face (because you are going to get rejected!). In the morning is where I have the most energy, and I believe it is important I put myself in a good place mentally and physically if I want to have a productive day.

The goal of mindfulness is for me to achieve a state of alert, focused relaxation before my day starts, by deliberately paying attention to my thoughts and sensations without judgment. I find this useful as I feel it allows me to be present at the moment hence making me feel more engaged when it is time for me to crush some work.

Exercise is what I use to physic myself up. I am not really into weightlifting, I do calisthenics (including freestyle) which requires a lot of energy. Whilst I am training, I often listen to podcasts (i.e. Towards Data Science Podcast, The Chai Time Data Science Podcast, The Artist of Data Science, etc), but if it’s a day I don’t feel like working out, I have a playlist for that – It’s rough.

6.55–7.55: Reading

I am one of those read a book a week guys, but this slot isn’t necessarily for books (although I keep a book with me everywhere I go so I can squeeze out some pages while I wait). This slot is allocated for reading blog posts. Throughout my day I usually save interesting blog posts I find online and it’s this time I read them (therefore I am reading the post I saved from the previous day) – I find this gets me mentally prepared as I am often inspired by the work of others.

8.00–12.00: Data Science

If I am volunteering/freelancing, or I have a personal project I am working on, it fits in here. I believe whenever I am doing a programming task I ought to block out a large chunk of time so I can really get lost in the work – the state of flow kind.

Currently, I am working on a personal project where I am "Using Machine Learning to Detect Fraud". The goal of this project is not so much to attain an accurate model, instead, I am focusing more on other stuff such as the Machine Learning architecture (train by batch, predict on the fly, serve via REST API in this instance), Continuous integration and deployment pipelines, deploying to PaaS without containers (i.e. Heroku), and deploying to IaaS (i.e. AWS ECS).

Using Machine Learning To Detect Fraud

Taking that into account, I am aiming to put heavy emphasis on software engineering best practices since I believe "Data Scientist Should Know Software Engineering Best Practices".

Data Scientists Should Know Software Engineering Best Practices

12.00–1.00: Lunch

Yes, I block out Lunch. Blocking out time to diffuse is just as important as having a focused time. I am not going to go into why but a book I’d recommend is "Learning how to Learn".

Note: I do not do affiliate marketing so any links I do to purchase a book is just a recommendation because it was useful to me.

1.00–3.45: Blogging

I prefer to sit with a blog and get it all written in a day so I block out a 2 hour 45-minute block of straight button bashing.

You are probably thinking "how do you get time to come up with ideas for your blog?" or "what If you need to code?". The short answer, I have quite a lot of optional time after Dinner to do as I plea, even if it is blocked out as something else, but in general, I believe I’d need a full article to answer those questions accurately.

3.45–4.30: Social Media

This one is important because I always go on about building a Data Science network.

Networking is important, but it is not a substitute for hard-work!

I am grateful that my blog post are growing in popularity and with that naturally comes people who want to speak with you and honestly it is amazing the number of cool people you meet. However, it becomes a problem when this consumes you.

Yes, you want to network and meet new people. Yes, you want to answer all the questions people have for you with good quality. Yes, you want to see cat pictures on your feed, but the ultimate goal is developing yourself into an elite Data Scientist, hence you ought to set your boundaries and stick by them.

Note: I also go on social media during my lunch, although this is usually more for leisure and cat pictures.

4.15–6.00: Learning

If I realise I need to learn a new framework for my project, or I am taking a course, or I am going through a research paper, or I want to write about something I haven’t tried before… It all goes here.

3 stages of Learning Data Science

6.00: Crash Stop

At this point, I have diffused from work mode and anything else beyond this point is pure leisure or taking care of responsibilities.

Now that I am currently unemployed, I use this time (usually 6.30–8.00) to apply for jobs since I know people in the UK will be finishing work and we can spark up longer/deeper conversations -How that correlates? I don’t believe the only way to get a job is by filling applications.


Wrap Up

In my opinion, having a structure is the foundation for a productive day. Additionally, in a time of mass uncertainty, especially for those that have been laid off, I believe people must take time to consider their mental and physical health as well as their careers. "Getting a Data Science Job Is Harder than ever" and will require some urgent patience whilst you develop yourself. As a fellow Unemployee, my best wishes to you all seeking work.

Stay active, and have fun!

P.S. Dhruvil Karani wrote an excellent article regarding the job search that I believe everyone should read – "Getting fired and hired as a Data Scientist in the middle of COVID-19"

Getting fired and hired as a Data Scientist in the middle of COVID-19

Let’s continue the conversation on LinkedIn…

Kurtis Pykes – AI Writer – Towards Data Science | LinkedIn


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