How to secure a data science job in 2021, success stories from getting jobs at Microsoft, FedEx, Impact Startups, and more. When you combine data science, collaboration, and real world data beautiful things happen.
I know you don´t have time so let us jump right into it.
Data indicates the data science market is getting flooded with too many data scientists. There are dozens to hundreds of applications for positions, and in that sense competition is very high.
But in another sense, there are many job openings. This disconnect is because while many people call themselves data scientists, not many people are capable of meeting the demands of most jobs in the profession. It requires a lot of difficult-to-come-by training, hard and soft skills, which is not something you can pick up with a few months of courses or a one year masters program.
The lack of “Real-World Data Scientists” is one of the reasons, we started Omdena, a collaborative platform in 99 countries where data scientists and engineers from different backgrounds and experience levels develop their skills, build real-world solutions, and make an impact.
Apart from technical skills, especially data engineering, even the most technically skilled data scientist needs to have the following soft skills to thrive today. All of which you can only learn through hands-on projects.
- Cultural empathy
- Creative thinking/problem solving
- Presentation skills
In the following I share five success stories from Collaborators who completed several Omdena AI Challenges and then secured jobs at various companies.
I am sure you´ll be inspired in your journey by reading the magnitude of perspectives and learnings from these amazing changemakers.
Becoming a Software Engineer at Microsoft: A Journey of Growth
On the value of failure
I can’t really pin down one big failure, there have been quite a number of setbacks I have had in my career that leave you questioning whether you are good enough?
Other struggles I have faced are the common ones that most people struggle with within their career or work environment; stress, over-working, or feeling overwhelmed at times.
But what I can say is I learned one major thing, which helped me to get through obstacles with more confidence, calmness, and clarity.
Learn to accept setbacks as part of the process
Accept it and just move on. There are things that you can’t always control as there are always external factors involved. And you will never be the master of external factors. This is a great illusion.
If things are meant to go sideways they will always go sideways. The good thing is you will learn a lot from the sideways as the most important lessons are often hidden in going “off-track”. It makes you reflect on yourself and the situation you have been in. So the question you can ask yourself is, What can I learn from it? And then you move on to the next endeavor. One step back, and two steps forward.
Getting a Data Science Job Offer at Accenture (Interview Skills Are Not Enough…)
On the value of communication skills
While you appear for a data science interview, apart from revising basic ML concepts such as Classification, Regression, evaluation methods, sampling methods, etc., it is also important to be able to explain the kind of data science projects you have done in the past. Having applied hardcore concepts in a project and not being able to explain it to the recruiter makes little sense. In this way, you need both the communication skills and real-world experience under your belt.
#Key tip: Improve your communication skills early on
Think about how to communicate your results to a non-expert or non-technical person. What problems are you solving? What impact is your solution making? How does it improve a process/ a person´s life etc.?
From Omdena to a full-time offer at Microsoft
On the value of leaderships skills
Kritika Rupauliha is a CS undergrad, currently in the 6th semester of her degree. She has worked at organizations like Leading India AI, Reflex Solutions LLP, Omdena, IIIT Allahabad, and Microsoft as an intern.
At Omdena, she worked her way up from Junior ML Engineer to the Lead ML Engineer of a project. This was her first time managing a task with a large number of globally diverse participants. According to Kritika, by participating in an Omdena project, she learned to balance between empowering people to take their own initiative and get things done, while at the same time setting goals to keep the overall task on track. She also gained valuable skills in clear and regular communication, especially while working remotely. She learned to manage work for Omdena, her day job, and family commitments, and also to manage notifications appearing round the clock because of the global nature of the collaboration.
“Before joining Omdena, I had been involved in some research work and college projects under my professors. But I had never been exposed to such a big community of similar-minded individuals. I found out that I thrived in such a community, learning with my peers, and exploring the horizons of AI. Omdena is also the reason why I got selected for a software engineering intern at Microsoft.” — Kritika Rupauliha
For Kritika, being around experienced professionals and learning from them was the best thing, and they went on to become close friends who will always mentor her in her future endeavors. She learned valuable communication skills for which she credits her projects at Omdena.
Transitioning Into a Data Science Job in 12 Months
On the value of embracing the unknown and leaning into fear
Rosana de Oliveira Gomes is an inspiring Astrophysicist who is now a Lead Machine Learning Engineer at Omdena.
If you would start all over again. What would you do differently?
I’d definitely spend less time ‘on the fence’.
When you are changing careers, it is really important to embrace the new path. I spent a very long time identifying myself as a ‘Researcher in Astronomy changing careers into Data Science’ rather than calling myself a Data Scientist, even when I was working in Data Science projects for a very long time.
Whatever path we choose in life, it is extremely important to have a support system, so we can lift each other up and celebrate every single step of the way. The same is true for careers in data science.
Find your kind of people and make sure to have fun with them on your data science journey. They will be the friends who will spend days with you trying to figure a way to improve models performance, who will recommend the best new AI courses out there and who may be one day the ones that will recommend you to a wonderful job.
Getting A Senior Data Scientist Job at FedEx
On the value of passion & purpose
Juber Rahman is a researcher in the field of Electrical and Computer Engineering turned Data Scientist who believes in the power of passion.
What was the best advice you got from someone in Data Science?
To learn basic software engineering in parallel to machine learning. The job of a data scientist includes a lot more skills other than model development. For example, a good understanding of data pipelines, database systems, cloud frameworks, and object-oriented programming.
“I believe a person performs the best when he or she is passionate to solve a problem. Very few organizations (e.g. Omdena) can ignite the passion in you. Most organizations make it feel an obligation to do something rather than creating a drive to solve a meaningful problem.”
Shifting career in a 90 degrees direction
On the value of being ok in chaos
I have been involved for a long time in Business analytics and controlling, and now I’m taking one step further earning a Master’s degree in Business Intelligence and Data Science.
Doing AI for Good (1) on a global scale (2) and with a global team (3). Those were the 3-ingredient salad that made me want to participate in such an exciting project.
I improved a lot of data engineering, tools for feature importance analysis, hyperparameter tuning, and cross-validation techniques. And I also learned about neural networks.
Mainly improved skills in Python and in using libraries such as Scikit-Learn and visualization libraries such as Seaborn.
About soft skills, I improved team management skills, mainly because we were a very diverse team with different cultures and backgrounds. I also learned that having a passion for a topic is crucial for self-initiative. I also learned to swim in a world of chaos (at the beginning of the project) and to be patient for things to come into place so that we can work in a structured project, with clear tasks, with clear responsibilities. I also learned that it doesn’t matter if you try something that maybe later it’s not part of the pipeline of the project. It’s part of the learning process.
There is a lot of smart people out there willing to help and to make good using AI. Being part of such a community like that makes me proud of it. Makes me want to share it with my relatives and friends.