What Employers are Expecting for a Data Scientist Role in 2020
Data scientist role expectations seem to change regularly. There are so many new avenues that a data scientist can explore for a job, and each industry and company will come in with their expectations. Knowing the typical data scientist's duties can make a difference in how well you can perform your job. Some of the responsibilities that a data scientist is expected to play in 2020 includes:
The Technical Skills
Employers will expect any data scientist they hire to have a variety of technical skills. That is why about 40 percent of data scientists' positions will require at least a master's degree in the field. With the right technical skills thought, it is possible to get these positions with just a bachelor's degree. Technical skills that are in demand in 2020 include:
It is vital to the daily work of a data scientist. This skill allows the professional to turn massive walls of textual and numerical information into forms that are easier to digest and understand. It may include graphs, maps, and charts. While rows and rows of data in any way may be difficult to understand, a data scientist can use data visualization to sort it out and make it easier to read and see patterns.
While any programming language experience can be useful, data science has taken off with Python. Many of the machine learning algorithms found in data science do well with Python, and Python has many extensions and libraries that do well with data science. It is also a relatively simple language to learn. Employers will likely require Python in their job descriptions and for the data scientist duties in 2020.
Python will be useful when exploring all of the critical data that a data scientist will need to work through and find meaningful patterns. However, SQL is another functional programming language to know. It is the language that will help the professional create and search through large datasets. Any employer who hires a data scientist will have their dataset, and this dataset likely relies on SQL to function. Knowing how to use this language will help the data scientist experiment and move around the data as necessary.
The Fundamentals of Statistics
While data science and statistics are two separate fields that do not overlap much, it is still crucial for a data professional to know at least the fundamentals of statistics to see results. It will help them when it comes to gathering, organizing, analyzing, and interpreting any data they need for a company. That will help them use their other math skills to create statistical and mathematical models for any data they need.
Social Media Mining
There is no way to get a job in data science without some rudimentary knowledge of mining social media. Social media has a ton of valuable information that all companies want to get ahold of. And since so many customers will spend their time visiting, commenting, and interacting with social media. It is the perfect place for companies to learn something new, and data scientists are expected to know how to gather that information.
Not only will data scientist duties include machine learning, but also Natural Language Processing (NLP). It is a subfield of artificial intelligence meant to help bridge some of the gaps that show up between machine understanding and human language. It is essential to advancing the functionality of AI, and without AI, it is almost impossible to make the algorithms you need to sort through all the data.
Along with the other skills above, all data scientists will need to know higher levels of math. Data science includes a lot of math, and having a higher-level understanding of math will help provide you with the skills you need. Some of the best math skills to have for this position include statistics, linear algebra, and multivariable calculus, to name a few. The more math you know, the better you will do in this position.
The Non-Technical Skills
In addition to some of the technical skills that we listed above, companies will have other data scientist role expectations that are important too. Some of these include:
If you cannot work in a team, then data science is not the job for you. Data scientists need to work with almost everyone in the company for the best results. They need to play well with others and receive help and advice from others. They may need to work with several departments to see results and make sure all the datasets are complete and accurate. Without teamwork, the data scientist will never get anything done.
After the data scientist has taken the time to gather, sort, and analyze the data they receive, they must have a way to convey all the conclusions they collect. That needs to be done without all the technical jargon that the key decision-makers may not understand. Excellent communication skills to discuss things and findings, and to explain where those conclusions come from are critical to success in this field.
It may not seem like an essential part of the game, but it can make or break a career for a data scientist, and their employer will expect them to be set here. Not only should you apply all of the knowledge you have for handling data, but you must be able to explain how any conclusions and theories you come up with can be used to help benefit the business. They need to understand the industry and the market where the data comes from and look not just for insights but also for promising ideas that can help the company succeed.
It takes a good deal of business knowledge to work with, as well. It is sometimes the hardest part for a new data scientist to learn how to work with. But for the right professional who can handle business knowledge and all the technical skills, there are ample job opportunities available.
The data scientist role expectations are ever-changing, and all data science professionals are expected to come in prepared with many skills to impress their future employers. But for those professionals who possess these skills along the way, there are endless job opportunities available to them, and many fun projects to spend time on.