Why Companies aren’t looking for Data Scientists — The Holy Grail of Data Science Career
Have you ever threw yourself into the interview process and failed? Here are the ten secrets increasing your odds of getting a dream job.
Do you find yourself stacked in business intelligence reporting, data pipelining, or software engineering routines and feel that you were born for something more?
Or, did you ever get rejected from the candidates’ pool, and you feel that you have done everything right?
Those situations appear from time to time and force us to think about what we could do better or differently to get a dream job or contract.
It is not only about building hard and soft skills, learning about the potential employer or client, and practicing interviews. It requires holistic reflection around ten key concepts to make it happen. Let’s explore the first one in this article.
1. Firms are not hiring Data Scientists
This subtitle sounds crazy as, according to Gartner, it is the sexiest job in the 21st century.
Has the hiring manager ever asked you if you are a good data scientist?
Most probably not. But he would certainly ask how you would improve the accuracy of convolutional neural network recognizing faces if you would be applying for the position of computer vision engineer. It could be a start-up entering a market with a new face recognition solution for smart buildings.
Becoming a passionate problem solver and expert in a particular industry is the key to success. Think about the following questions to find your niche in the broad data science universe:
- What area of data science excites me?
- What industry do I want to be in?
- What are the major trends affecting my ideal profession? How might it change in the future?
- What hot topics in my field I should address to stay competitive?
- What is the compensation ranges of my target profession?
- What education and training are required?
Imagine you are a Digital Transformation Director working in an e-commerce firm. You are looking for a person who will lead an initiative powering an e-shop with AI to increase revenue. Who would you be more interested in talking to?
I am a data scientist with wide and deep ML and AI knowledge with 3 year of experience. I am looking for the opportunity to advanced my carrier in senior role, where I could lead a small data science team.
I support retailers to improve their digital marketing ROI. I built and deployed customer propensity models and increased revenue by 2M$. Writing a blog about the latest AI research in e-commerce is my passion. I am looking for the leadership opportunity, where I could deliver AI solutions driving consumer personalization across all sales channels .
Two introductions above may refer to candidates with similar experience and skills. The only difference determining losing or winning is that the winning one is walking in the hiring manager's shoes.
Call to Action
How are you currently positioning yourself to potential employers or clients? Does it sound more like seeking a job or emphasizing the value and passion you can bring?
Exploring the professional environment will sharpen your value proposition and make you stand out in candidates' competition. It is the first concept to keep the interviewer interested in talking to you. How? Follow the actions below:
- Create a list of your values, interests, and skills
- Search job descriptions containing your list items
- Select the industry that interests you
- Build a list of target job titles
- Investigate the compensation package in your area for selected job titles
- Study the ML and AI trends within selected industry
- Work on industry project and publication portfolio
- Design a list of needed skills tailored to the target profession and industry
Remember linking your identity with the target industry is a key to open many doors.
Do you find the hiring process necessary evil to do what you love?
Whether you are climbing a career ladder or just breaking into the field of data science, we all face technical and behavioral interviews, where we need to prove ourselves. The pain starts when the stress or fear of rejection comes into play.
What can be a hell can become heaven once you obey ten hiring commandments before standing in front of Saint Peter. Let me know which one of the remaining nine you would like to read next:
2. How project management can benefit you to get a dream job
3. The secrets you must know to get 1st interview in the dream company
4. The one thing to avoid being screened out during a job interview
5. How you boost your chance of getting the dream job by ten times
6. Why data scientist doesn’t get the job using the “apply” button
7. What are the right data science interview questions
8. What to do if you do not get a response to the job application
9. How data scientist can make a thousand euros in a minute
10. What can go wrong after getting the dream job