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# Introduction
After I first began my knowledge science profession in 2020, the sector was booming. In all places you regarded, firms have been hiring knowledge professionals. At the moment, I constructed a knowledge science portfolio and managed to land a number of high-paying purchasers.
I’d write knowledge science content material, similar to white papers, articles, and technical documentation — which paid between USD $500 and $1,000 for 2 days of labor. I constructed easy machine studying fashions and performed analyses utilizing instruments like Tableau and Energy BI. As purchasers began recommending my work and leaving constructive evaluations, I landed extra initiatives. I labored 5 to six hours every day from my sofa and was utterly distant.
Lately, nevertheless, I’ve modified issues up.
I’ve stop a number of freelance jobs for a full-time knowledge science place — one the place I am going to the workplace daily and work double the hours. And no, it isn’t as a result of the job pays extra. In actual fact, I made more cash as a contract knowledge scientist than I do now.
So why did I change from a cushty, high-paying freelance job to a full-time place that pays much less?
Learn on and you will find out the three high issues that led me to taking this motion.
# 1. Constructing Technical Abilities
After I labored for myself, I noticed I might hit a plateau in studying technical expertise. I used to be working extra like a machine, producing repetitive outcomes for a similar freelance purchasers. This meant that I not solely labored much less, however my technical information had reached a standstill.
A actuality examine got here once I attended a good tech convention and networked with different knowledge professionals. I noticed I hadn’t saved up with a lot of the know-how they mentioned. These knowledge professionals have been constructing AI brokers and retrieval-augmented era (RAG) programs, whereas I used to be refreshing the identical dashboard for the hundredth time and writing white papers on Python for knowledge science.
Do not get me mistaken — a knowledge scientist’s worth is within the outcomes they drive, and in lots of circumstances, fancy instruments like massive language fashions (LLMs) are akin to utilizing a sledgehammer to crack a nut. Nonetheless, I lacked primary information of instruments that have been on the forefront of tech firms, and that scared me. I’ve witnessed firsthand how complacency and the unwillingness to adapt to new instruments has rendered tech staff out of date.
# 2. Being Paid to Study
At my present full-time job, there are coaching programs led by AI consultants that train you to combine LLMs into your knowledge science workflows. Common hackathons with groups like knowledge and software program engineering help you achieve ability units that transcend your scope of labor. There are peer-led tutorial classes nearly each week the place different crew members stroll you thru an issue they solved and present you easy methods to construct an identical mission. This protects a ton of time and teaches you way over most on-line programs.
A full-time job is the one place the place you study on someone else’s dime, as a substitute of getting to enroll your self in a $1,000 bootcamp.
After I targeted solely on freelance work, two issues occurred:
- Firstly, I wasn’t incentivized to study new issues until a shopper had an issue that required me to upskill.
- If I did must study one thing new, I sometimes paid for a web based course.
And if I obtained caught or did not perceive one thing, I did not have anybody round who might assist me grasp the idea.
3. AI-Proofing My Profession
This is likely to be controversial to some, however the largest motive I obtained a full-time knowledge science job is as a result of I consider it’ll assist safe my profession from AI. And whereas this would possibly sound counterintuitive, hear me out.
With my freelance job, this is what I discovered:
- Methods to use my present expertise to unravel the shopper’s downside
- Gathering shopper necessities and utilizing them to unravel a selected technical problem
Nonetheless, with a full-time job at a big tech firm, my scope now includes:
- Gathering a enterprise requirement and dealing with groups like product, design, and engineering to show it into a knowledge downside
- Making key product selections
- Understanding how the corporate’s knowledge warehouse works and utilizing it to construct knowledge pipelines
- Constructing relationships with stakeholders and friends
With freelance work, you sometimes resolve a focused technical downside for the corporate — similar to constructing a dashboard and refreshing it each quarter, or making a machine studying mannequin for a selected use case. The necessities are clearly specified, and also you simply must concentrate on execution along with your technical expertise.
Nonetheless, AI is democratizing technical expertise.
It permits individuals who do not know easy methods to code to construct purposes. Individuals who do not know SQL can simply write a question and create a complete dashboard. As AI continues to democratize technical expertise, the worth of information science freelancers will probably decline. The pay will lower, and the house will develop into extra aggressive.
Conversely, a company function is multifaceted. It requires way more collaboration, area experience, essential pondering, and understanding of the enterprise. As you climb the info science company ladder and attain greater positions inside the firm, you may develop into tougher to switch (at the same time as AI fashions get higher). Additionally, you may transition to roles like enterprise analyst or product supervisor and even negotiate greater salaries. To place it merely, there are numerous methods to maneuver ahead in a company function. You’ll be able to oversee knowledge options and drive enterprise worth in ways in which do not overlap with AI’s capabilities.
Alternatively, working a contract job the place the one worth you convey is your technical ability places you in a weak place.
For that motive, I’ve determined to prioritize long-term profession security over short-term revenue. I selected a lower-paying full-time job over freelance knowledge science roles to construct a set of expertise that can preserve me related within the subsequent decade, no matter how AI impacts the technical facet of the career.
Abstract
To summarize, I stop my snug, high-paying freelance roles to take a way more demanding full-time knowledge science job. And I did it for the next causes:
- To study technical expertise at a quicker tempo
- To climb the company ladder and prioritize long-term monetary stability over short-term revenue
- To safe my profession from AI by gaining expertise and studying expertise that can not be changed (similar to enterprise and product information, stakeholder administration, and significant pondering)
YMMV, nevertheless, so I encourage you to do your personal analysis. Drop a remark under if you happen to really feel you’ve got precious perception for others.
 
Natassha Selvaraj is a self-taught knowledge scientist with a ardour for writing. Natassha writes on the whole lot knowledge science-related, a real grasp of all knowledge subjects. You’ll be able to join together with her on LinkedIn or take a look at her YouTube channel.
