The Most Trending Job On the Market : New Born Data Scientist
Decoding the Complex Landscape of Data Science and Artificial Intelligence Jobs: A Data Scientist’s Perspective on New Born Data Scientist Roles
You’ve probably noticed that job descriptions for data scientists are getting more complex by the day. Like an ambitious director’s cut of a sci-fi movie, they sometimes seem to demand a character who’s half-wizard, half-rocket scientist.
Ever felt confused by a job posting that says “Entry Level Data Scientist” but asks for years of experience? This odd contradictions and sky-high expectations in today’s data science job market is really funny sometimes.
In this article, we decode one of these job descriptions, that actually taken by reddit post, take a humorous look at what “New Born Data Scientist” might mean, and try to navigate this complicated landscape.
The Evolution of Data Science Job Descriptions
Remember when a data scientist was simply expected to know some programming and statistics? Those were simpler times.
Now, it’s like expecting Frodo from “The Lord of the Rings” to not only carry the ring but also be an expert in martial arts, diplomacy, and Elvish literature.
Job descriptions have evolved into multi-page documents full of jargon and high expectations.
The Skills Gap: Reality vs. Job Posting
Job postings often read like a wish list that even Santa Claus couldn’t fulfill. They ask for expertise in Python, Java, SQL, and sometimes even quantum computing.
Yet, the daily tasks may just involve basic data analysis and reporting. This creates a gap between what is sought and what is truly needed, complicating the hiring process.
Entry Level Data Scientist
This post is the one that inspires me to write this article. It looks like this company is seeking an entry level data scientist.
However, even if they seek applicants in entry level, they want 4 years of experience, let’s check the image below.
If an entry-level data scientist is expected to have 4 years of professional experience, where should they start?
I’m confused. There might be something else in this job description that I’m missing, but I’m pretty sure I’ve seen other entry-level job descriptions that ask for much more.
Let’s write a job description. This one will be relevant in a year if things continue as they are today.
New Born Data Scientist
Our big-tech company serves Forbes 500 clients and occasionally dials Elon Musk on his personal phone (he hasn’t answered, yet!). We are now seeking a New Born Data Scientist — someone born just yesterday but ready to take on the tech world today.
Skills Required
Expertise in Multiple Programming Languages: You should be skilled in Python, Java, SQL, and R. Basically, be a programming polyglot.
Educational Background: A Master of Science in a relevant field is essential. Whether it’s Rocket Science, Data Science, Computer Science, or just “Science,” we’re looking for the best of the best.
Good to Have
On-Call Babysitter: As a New Born Data Scientist, having your babysitter on standby would be a plus.
Rapid Language Acquisition: The ability to communicate effectively using words within a year is highly desired.
Eyes-Closed Expertise: Experience in building deep learning models while blindfolded or with eyes closed showcases your true mastery of the subject.
Recommendations: Bridging the Gap,
In the competitive arena of data science, I think both employers and job seekers can benefit from setting and managing realistic expectations.
For Employers:
Clarity in Job Descriptions: Keep your job descriptions as clear and straightforward. Confusing or contradictory requirements can alienate potential stars for your team.
Realism: Asking for a “New Born Data Scientist” with a Ph.D. and 10 years of experience is as improbable as time travel in movies. Be realistic in what you require versus what you desire.
For Job Seekers:
Focus on Transferable Skills: Your background in another field might just be the plot twist your career needs. Don’t underestimate the value of transferable skills.
Be Realistic: Doing the Titanic Prediction dataset in Kaggle won't make you a Machine Learning Master. You can not do everything by googling, so be honest on your CV.
Continuous Learning: Technologies evolve quickly. Being committed to lifelong learning is important. Learning tools like ChatGPT or other Chatbots can help you complete your tasks more quickly and accurately.
Final Thoughts
As the data science careers continue to evolve, so do the job descriptions that come with them. While it may seem as if we’re in a comedy film filled with plot twists and unexpected turns, it’s essential for both employers and job seekers to read between the lines.
For employers, it’s about crafting job descriptions that are as clear and engaging, without the false advertising. For job seekers, it’s a call to be adaptable, ever-learning, and honest in their own career story.
Thanks for reading!