Nowadays, data science field is hot, and it is unlikely that this will change in the near future. While a data driven approach is finding its way into all facets of business, companies are fiercely fighting for the best data analytic skills that are available in the market, and demand for Data Science roles is going in overdrive. Also, this not a breaking news, lot of professionals are already working or are trying to get a job in the industry.
In my experience, I have seen many students who reached out to me to consult about what they could expect on their first job in the data science world.
In this article, I would try to share my experience and learnings with a peek into my own hardships and accomplishments during this journey.
It has been more than 2 years that I am working as a Data Scientist and it has literally been a roller-coaster ride. This is my first article ever, through this I would be sharing my exciting journey from being a fresh college graduate to a professional Data Scientist (The Sexiest Job of the 21st Century). I hope that my learnings might help you and give an insider view before you enter this amazing world of Data. I will be talking about the following milestones from my journey:
1. Rigorous Trainings
2. Know your client
3. Collaboration and Learning from your peers
4. Share your hard work
6. Importance of QA
7. Keeping an eye on your personal learning curve
Whenever you start a new chapter of your life, this thought always hits you “OMG, How would I do it?”, answer is, you need to train, and that’s what I did for first 3 months of my job.
Companies invest a generous amount of money on such graduate training programs, from getting the best facilitators and courses available to even paying new joiners for just sitting through trainings. The curriculum was a mix of technical and some behavioral trainings. As a group of freshers from various top colleges, we sat through a lot of trainings together varying from python, pyspark, SQL, statistics, Machine Learning, presentation skills, college to corporate training, email writing, company’s different business units and its own products. Most of these trainings were followed by innovative evaluation tests. For one of the training, we visited a retail store and presented our understanding about a category (My group got Breads and Breakfast).
In my opinion, these trainings are really helpful and should be a must for all new joiners. Because they really opens your mind and persuade you to think about end users when you come across different business problems ( Which is not exactly what is taught in universities ) .
After 3 months, I felt confident about diving into the real business. These trainings not only polished my skills but also gave me a group of friends, who were going through the same phase and that helped us bond together.
Client’s business is now your business too
After these trainings and evaluations, we were all assigned teams which worked for different clients across the globe and that too in different business units and I got one of the best “PERSONALIZATION”. My team supported a North America based retail client with its loyalty campaign execution and evaluation.
I was so excited to get my hands dirty with coding and model building. But wait, you cannot just start working, you need to know about your client, because as the subheading reads, it is your business too. For this I did an exercise called “Health check of your client “.
Health check of your client
This was part of my team onboarding plan. I learnt about the client’s history, top management, other businesses, competitors, partners, acquisitions, latest news and the basic KPIs like sales, visits, units, customers etc. and created a power point presentation on the same and presented it to my team.
Why do it?
While doing this exercise I was also attending team meetings and that was when I realized why it is important to know the client first because then only you would be able to align your thoughts and your work with client’s long term and short-term goals and as a result you would be able to dig into the right numbers and share it right way with the client.
Learn from all those brilliant minds around
Becoming a good Data scientist is not only about technical skills like coding and machine learning. There is a lot of other skills one should know, to not only become a good data scientist but also a good professional, like time management, collaboration, working with colleagues outside your team, participating in team meetings, sharing your work, sharing your thoughts in brain storming sessions and office level meetings and a lot more.
Your thoughts would be “Please don’t say I have to sit through more training exercises for this! “answer is No! You don’t! You just need to look around! There are a lot of people around you, who are practicing these skills day in and out from many years in this corporate world.
Believe me, there is a lot to learn from all these brilliant minds around you and most of them would be more than happy to have a conversation with you and I assure you that you would feel enlighten even after a small conversation with them.
One big people skill which I learnt was how to react to or talk about a pressure situation at work. When I did that first mistake in my deliverable, I felt troubled, scared and sad. I was feeling so uncomfortable to go in a meeting with my manager on it, but my team buddy came to my rescue and talked me out of all those bad feelings and asked me to go in the meeting with a plan which caters to the factors involved in the mistake as well as ways to not repeat it again in the future. I took the advise and went in the meeting confident, taking responsibility of my work but not sounding guilty and even with a plan to prevent any such miss in future.
Make your message land right
There’s a saying among public speakers: “It doesn’t matter what you intended to say. It’s what landed with the audience that counts.” It’s true — the only thing that matters is the message you were able to get across to your audience. Whether you’re giving/ receiving one-on-one feedback, brainstorming with your team, or giving a major presentation, it’s the message that lands with your audience that counts.
The next big thing I learnt was owning my work and then presenting it to the stakeholders in a way that shows the effort I spent to steer the project in the direction of desirable conclusions/ outcomes and that too in the language they understand.
For example: You build a model to predict the customer churn, now when it comes to what you should share, the stakeholders are not interested in which model you used or which validation technique you used. They would just be interested in the factors responsible for the churn and what actions could prevent or reduce it. So, the final deck should have the actionable insights and plan to move ahead but not the details on model and its parameters (Exceptions are always there).
This is where your hard work will speak, and you should always spend time on bringing the best you can in creating these slides and presenting them.
It’s also critical to remember that the people you work with are listening to you in many different ways. Yes, they hear your words, but they’re also watching your body language, monitoring your intonation and observing for any subtle signals you send, that’s why you should not shy away from a few dry runs.
Business As Usual
It is the normal execution of standard functional operations within an organization. As we all know, it’s not always sunny — similarly, you would not be building ML models every day. Most of the days you would be working on BAUs, like measurements, updating dashboards or reporting etc.
Yes, obviously we don’t wish to do this most of the time but supporting the business is our topmost priority and these reports act as pillars to company’s strategic planning and decisions.
So, my suggestion would be to keep a good balance of the type of work you do. To do so, clearly communicating your aspirations, requirements and suggestions with the manager is the key. This would save you a lot of time and energy on just cribbing and gossiping :)
Data Quality Assurance — A tedious task but a huge time and credibility saver in long term
While doing this sexiest job of the century, there are many things that could go wrong, and the only way to know that a system/model will work correctly is through QA.
Testing is one of those deceptive activities which takes more effort in the short-term but have big and fruitful impact in long-term. And as the sub- heading reads, it also increases your credibility and confidence in your work.
You should always have a QA framework in place which would check everything from input to final deliverables. There are several common types of useful quality tests that identify bugs, confirm working components, and investigate the system’s/model’s expected behavior, apart from these automated tests, you can always create manual QA checks relevant to your project/report.
I learnt this the hard way, but take my advice and always self QA your work with a framework at hand and get it QAed with from someone else too, because sometimes we just miss the bug because we created it and a second pair of eyes could save the day.
Never forget why you started in the first place
Learning does not end once you graduate and get your dream job, as learning is a lifelong process and your dreams are getting bigger every day. You can continue learning through online courses, any media channel by subscribing to informative resources, reading about latest industry news and applications from sources like Medium or LinkedIn and more. There are always new skills to learn and strategies for you to adopt, and you should never stop learning as it enables you to:
· Generate new ideas — do not just stick to what you know. Learn and generate new ideas by listening and watching out for any new resources from which you can gain new knowledge and concepts. Reading books also helps.
· Keep your passion — if you want to pursue your passion, you will find ways to enjoy it simply by learning more about it.
· Converse better — the more you learn, the more knowledge and ideas you can share with the people around you.
· Banish boredom — learning keeps you busy and it helps you to spend time productively.
· Create a stronger work-life balance — studying will help you overcome job burnout, allows you to pause, and regenerate energy.
· Improve your brain health — learning is a brain exercise. You will avoid Alzheimer’s disease by constantly using your brain and it will give you a long life.
Learning is key to living a fulfilling life and having a successful career. Whatever you want to learn, you can learn. Get out there and increase your knowledge and never stop.
I cannot say that all Data Scientists across the world would agree with my perception of entry in the industry because this is just my journey, and everyone has their own path and experience.
I would conclude by saying “All the best for future“ to everyone who is reading this because reading this article mean you are interested in pursuing career in this field. I can assure you that you would always feel challenged in this job and also inspired by all the great work being done in the industry.
Thanks for reading! 😊 I hope that you liked the article! Keep Learning and sharing knowledge. If you enjoyed it, please hit 👏. It will help other people see the story.