How to become a 21st century Data Scientist?
by Kamalika Some
July 24, 2020
Becoming a data scientist is a relatively new career path that merges statistics, business logic and programming knowledge. With the exponential amount of data being generated through our smartphones, desktops, and the vast array of IoT devices around the world, governments and private businesses are keen to learn from their vast data collection processes.
While data scientists can (and do) perform data analysis, they do so as part of building and deploying predictive models that often incorporate machine learning and deep learning protocols. Data scientists also need to have a meta-level understanding of which models are best suited to the data being analyzed. Since all models are approximations of current and future environments, they require fine tuning which, in turn, relies on the mathematical expertise of data scientists. Although data scientists are not data engineers, they should (ideally) have some knowledge of how databases are built and how to extract data from the database management system. (DBMS) preferred by an organization. Due to extensive knowledge requirements, including academic and professional training and / or experience, businesses, research organizations, and government agencies scramble to find qualified data scientists.
Read the ultimate guide to accessing the sexiest job of the 21st century-
Data scientists are highly educated – 88% have at least a master’s degree and 46% have a doctorate – and while there are notable exceptions, very good training is usually required to develop the in-depth knowledge needed to be a data scientist. To become a data scientist, you could earn a bachelor’s degree in computer science, social sciences, physical sciences, and statistics. The most common fields of study are mathematics and statistics (32%), followed by computer science (19%) and engineering (16%). A degree in any of these courses will give you the skills you need to process and analyze big data.
There are many different paths that can lead you to a lucrative and rewarding career as a data scientist. Most start at the undergraduate level, with a bachelor’s degree in data science that can lead to jobs as a data visualization specialist, management analyst, and market research analyst. From there, many students earn master’s degrees in fields such as machine learning algorithm developer, statistician, or data engineer. Many students go on to pursue doctorates in concentrations such as Business Solutions Scientist, Data Scientist, and Business Science Analysis Manager.
Learn to code
Thorough knowledge of at least one of these analysis tools, for data science R is generally preferred. R is specially designed for the needs of data science. You can use R to solve any data science problem you are having. In fact, 43% of data scientists use R to solve statistical problems.
Python is the most common coding language I typically see required in data science roles, along with Java, Perl, or C / C ++. Python is a great programming language for data scientists. That’s why 40% of those surveyed by O’Reilly use Python as their primary programming language.
Knowledge of cloud tools such as Amazon S3 can also be beneficial. A CrowdFlower study of 3,490 data science jobs on LinkedIn ranked Apache Hadoop as the second most important skill for a data scientist with a score of 49%. You must master SQL as a data scientist. Indeed, SQL is specially designed to help you access, communicate and work on data. It gives you information when you use it to query a database. It has concise commands that can help you save time and reduce the amount of programming you need to perform difficult queries.
Prepare your skill set
A data scientist can translate his technical and analytical findings clearly and fluently to a non-technical department. They should also be able to understand the needs of their non-technical departments (such as business development or marketing teams) in order to properly analyze the data. A data scientist must allow the company to make decisions by presenting solid and verifiable information.
Apply for Data Science Certifications and Get Your First Data Science Job
Obtaining a certification can improve your skills and make you a more marketable candidate. Potential certifications include a Certified Applications Professional, a Certified Cloudera Professional: Data Scientist, EMC: Data Science Associate, and a SAS Certified Predictive Modeler using SAS Enterprise Miner 7. Look for positions such as Junior Data Analyst or Junior Data Scientist. System-specific training or certifications in data-related areas (e.g. business intelligence applications, relational database management systems, data visualization software, etc.) may be helpful when developing looking for basic data science jobs.
Share this article
About the Author
More info about the author