My arms are expansive lifting out of the binds of that stress and fear clench no more. I breathe in the free air no longer stagnant, enclosed released from the glass; those holes in the cover never…
Hello friends! Last time we saw Top 10 Buzz Words in Data Science, today I will help you gain insights on Five Hot Careers in Data Science.
With so many different data science careers to explore, you might find yourself wondering which is the right one for you and if you’ve got what it takes to fit the profile.
The goal of this career guide is to arm you with that knowledge, so you can spend your time efficiently and end up with the data science career you want.
Four Pillars of Data Science:
To help you sort things out, I have featured the top 5 in-demand types of data science jobs .
Data Science’s Big Five:
Following are the major roles in the field of Data Science:
2) Data Analyst — a go-between for tech and business teams
Data Analyst translates the business problem to the data scientists, and later uses visualization to convert a trained and tested model and mounds of user data into a digestible format. Data Analyst ensures that data science teams don’t waste their time solving problems that don’t deliver business value.
3) Data Scientist — Clean, Explore, Train, Optimize, even Deploy Models
Data Scientist picks up a data set prepared by a Data Engineer, and perform the munging, EDA, model training, testing and optimizing, and sometimes he also deploys the model he creates.
4) Machine Learning Engineer — build, optimize, deploy
Machine Learning Engineer seems to have most of the tasks and technologies as he listed for Data Scientist, but with a bit more intensity to the model tuning, as well as integrating models with front-end Javascript apps.
Machine Learning Engineer needs solid knowledge of machine learning theory and understanding of deep learning in addition to Data Scientist skill set.
5) Machine Learning Researcher — finding new ways to solve challenging problems
Machine Learning Researcher is the person who would be so well-versed in math and statistics that he can develop his own algorithms that do more to solve a problem than one of the algorithms from popular packages, or maybe they are very creative in combining techniques.
Now that you are aware of the data science employment options, roles and career paths, you are equipped with all the knowledge you need to take the first step on your data science career journey.
Final piece of advice? Learn with curiosity and optimism. And don’t be afraid of making mistakes along the way. Just work hard, always do your best, and the rest will follow! Thanks for reading.
The journal Wilderness & Environmental Medicine recently published a set of clinical practice guidelines from the Wilderness Medical Society about the management of exercise-associated hyponatremia…
IT programming is undoubtedly a complex field, and not everyone is suited for it. To master it, you need a special mindset a lot of talent, and technical knowledge. But over time, many young people…
We have been stripped of the lives we knew — thrown into the lives we hate by keepers who do not know what it means to be kept. *Author’s Note: The Powerhouse introduced The Handmaid’s Tale to me…