3 answers
Arvaiya
Student
Rochester, Minnesota
7
Questions
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favorite part about Data Science?
What is your most favorite part about Data Science? Is there any fun task you favor?
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3 answers
Kyle Draper
Recruiter
7
Answers
Toronto, Ontario, Canada
Updated
Kyle’s Answer
Even though I'm not a Data Scientist myself, I've had the opportunity to hire for these positions recently. From the viewpoint of the candidates, some of the most exciting or challenging aspects included:
* Embarking on completely new projects crafted from the ground up
* Utilizing cutting-edge tools like natural language models or GenAI projects
* Conducting research that culminates in the launch of new products or features, which is often more rewarding and enjoyable for Data Science enthusiasts. It's thrilling to know that the work you're doing will be recognized by others, either immediately or in the future.
As the significance of natural language models and GenAI continues to grow, Data Science and Data Analyst teams will increasingly find themselves in the limelight. This may bring added pressure, but it also opens up the door to more intriguing projects and the chance to make a significant impact at a company-wide level.
* Embarking on completely new projects crafted from the ground up
* Utilizing cutting-edge tools like natural language models or GenAI projects
* Conducting research that culminates in the launch of new products or features, which is often more rewarding and enjoyable for Data Science enthusiasts. It's thrilling to know that the work you're doing will be recognized by others, either immediately or in the future.
As the significance of natural language models and GenAI continues to grow, Data Science and Data Analyst teams will increasingly find themselves in the limelight. This may bring added pressure, but it also opens up the door to more intriguing projects and the chance to make a significant impact at a company-wide level.
I appreciate your support, Kyle
Arvaiya
Tylor Mondloch
Data Science
3
Answers
Billings, Montana
Updated
Tylor’s Answer
After even a little bit of experience in data science, you develop a catalog of algorithms in your mind, like a toolbox. My favorite part is when I'm presented with a use case / problem, then investigate which algorithm can help to solve the problem. Sometimes we end up comparing the results of several algorithms and seeing which one is superior.
Another very fun part is when you get to read about a new algorithm. This is just like a carpenter or mechanic discovering a new or improved tool. And thinking through how that new algorithm can help you now and in the future.
This field just keeps on moving forward, so you're never bored.
Another very fun part is when you get to read about a new algorithm. This is just like a carpenter or mechanic discovering a new or improved tool. And thinking through how that new algorithm can help you now and in the future.
This field just keeps on moving forward, so you're never bored.
Bryan Cimo
Data Scientist
5
Answers
Fountain Valley, California
Updated
Bryan’s Answer
The best part of being a data scientist, for me, is the thrill of exploration and discovery. The essence of science is embedded in my job title, and it's what I find most exciting about this role. Most of the projects I handle involve some degree of delving into data or concepts and unraveling the reasons behind their state. I'm naturally inquisitive, and I thoroughly enjoy applying this trait in my work.
One task I particularly enjoy is working on projects related to artificial intelligence and machine learning. These systems captivate me because they involve teaching a computer to make decisions based on vast amounts of data. It's intriguing to observe how these systems interact. I find projects that involve predicting future events particularly fascinating. They add an extra layer of interest to my work.
One task I particularly enjoy is working on projects related to artificial intelligence and machine learning. These systems captivate me because they involve teaching a computer to make decisions based on vast amounts of data. It's intriguing to observe how these systems interact. I find projects that involve predicting future events particularly fascinating. They add an extra layer of interest to my work.