Slowly, in the shadows, Landing.jobs is adopting a data-driven mindset and I am honoured to help this group of fabulous people, who I now consider as friends, to take this leap of faith.
Being a young data scientist myself, I have a lot to gain from the experience as well, being able to develop both my technological and communication skills. During the first months of this new experiment, here are the 10 lessons I’ve learned:
1 . Start by Listening
Before even pitching ideas or explaining concepts, it’s quite a good strategy to just start by listening. Ask what the company and their people understand of data science and its concepts and what goals do they have. The outputs will give you valuable information to develop a plan and not waste time trying to “reinvent the wheel” or teaching people concepts they already know;
2. Be Prepared to Explain Things in Many Ways
Not everyone learns from the same examples or the same method of teaching. If you feel a concept you’re trying to explain has not been understood “quite right”, ask them what they didn’t understand and try changing the message content. Tip: soccer, video games, music and everyday things are fair game to explain difficult concepts! The beginning of this project started with a presentation on a meetup and a video with puppies so anything is possible! =) https://www.youtube.com/watch?v=vDa0z0gEvI4
3. Communicate
This should not have to be said but here I am. A data scientist is NOT the specialist in the data he/she is working on, the client is. Therefore, a fluent and regular communication between the parts is the secret to a productive work because a lot of times the things that do not make sense to a Data Scientist, make sense to the one that generated the data;
4. Be Upfront and Honest
Marketing is not the best helper of Data Science as many companies think they can go from zero to AI in less than six months. It’s your job as the first face of DS that the company is contacting with to be ready to dispel myths and set realistic expectations. Remember they don’t need an AI robot to enjoy the benefits of AI and talk to them about the work that baby steps can produce;
5. Do Not Be Too Serious or Too Uptight
Data Science is scary and quite complex to understand to many many people. If a silly evolutionary algorithm/neural networks can be used to teach a computer to play flappy bird and it is quite a fun way to explain the concepts, use it: https://www.askforgametask.com/tutorial/machine-learning-algorithm-flappy-bird/. Seriously, if you only speak in “data sciency” terms, people are not gonna understand you and will not be comfortable working with you;
6. Start Small
Any new project in data science should start by data analysis and data preparation. If the data is not in condition to be used to produce knowledge, it’s an old case of Garbage In — Garbage Out. The first task should always be to investigate the data and set a base for the work it is to come.
7. Evolve Slowly
Small steps with plenty of validation and lots of planning are better than one very wrong AI algorithm. Keep a plan on point and a register of your evolutions and the next steps will become clear over time. Do not overdo things, if a linear regression solves the problem, do it. You are there to help the company, not to show them how smart you are;
8. Don’t Be Afraid to Point Out Problems
The company should expect that the data will not be perfect and you are being useful when you are showing them what’s not so right, why and how it can be improved. Data Science thrives in objectivity and honesty, do not hide little things because they can become real avalanches of problems. To make this process easier, do not forget point 3 and foster an ongoing and trustworthy communication;
9. Difficulties are Normal, Solve Them As a Group
Every Data Scientist has hit “brick walls” many times over their lives. Being honest also means asking for help when you need it and accepting corrections and new ideas when they appear. People are not there to judge you, they are there to work with you towards a common goal, never forget that and work with the group, do not isolate yourself;
10. Have Fun
In all this list, this is probably the most important one. Remember why you started in the area and all the fun that happens in Data Science and you will conquer everyone around you with the enthusiasm! And when setbacks appear you will have a lot more strength to face them and overcome them.
Curious about where Data Science will lead Landing.jobs? So are we! This article is just the beginning.
Don’t forget:
“The Longest Walk of All Begins With Just One Step”
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