Becoming a data scientist is a relatively new career trajectory that merges statistics, business logic, and programming knowledge. Given the exponential amount of data being churned out via our smartphones, desktops, and the vast array of IoT devices throughout the world, governments and private enterprises are interested in gleaning insight from their extensive data collection processes.
While data scientists can (and do) perform data analysis, they do so within the realm of building and deploying predictive models which often incorporate machine learning and deep learning protocols. Data scientists must also have a meta-level understanding of which models are the best fit for the data being analysed. Since all models are approximations of current and future environments, they require fine-tuning which, in turn, relies on the data scientists’ mathematical expertise. Although data scientists are not data engineers, they should (ideally) have some knowledge of how databases are constructed, and how to pull data from an organization’s preferred database management system (DBMS). Due to the extensive knowledge requirements, including academic and professional training and/or experience, companies, research organizations, and governmental agencies are scrambling to find qualified data scientists.
Read the ultimate guide to gain an access to the sexiest job of the 21st century-
Data scientists are highly educated – 88% have at least a Master’s degree and 46% have PhDs – and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary 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 analyse big data.
Many different paths can lead you to a lucrative, rewarding career as a data scientist. Most start at the undergraduate level, with bachelor’s degrees in data science that can lead to jobs like data visualization specialist, management analyst and market research analyst. From there, many students go on to achieve master’s degrees in fields like machine learning algorithm developer, statistician or data engineer. Many students then pursue doctorate degrees in concentrations such as business solutions scientist, data scientist, and enterprise science analytics manager.
Learn to Code
In-depth knowledge of at least one of these analytical tools, for data science, R is generally preferred. R is specifically designed for data science needs. You can use R to solve any problem you encounter in data science. In fact, 43 percent of data scientists are using 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. This is why 40 percent of respondents surveyed by O’Reilly use Python as their major programming language.
Familiarity with cloud tools such as Amazon S3 can also be beneficial. A study carried out by CrowdFlower on 3490 LinkedIn data science jobs ranked Apache Hadoop as the second most important skill for a data scientist with 49% rating. You need to be proficient in SQL as a data scientist. This is because SQL is specifically designed to help you access, communicate and work on data. It gives you insights when you use it to query a database. It has concise commands that can help you to save time and lessen the amount of programming you need to perform difficult queries.
Brace your Skill Set
A data scientist can clearly and fluently translate their technical and analytical findings to a non-technical department. They must also be able to understand the needs of their non-technical departments (such as business development or marketing teams) in order to analyse the data correctly. A data scientist must empower the business to make decisions by presenting robust and verifiable information.
Apply for Data Science Certifications and Get your First Data Science Job
Earning a certification can improve your skills and make you a more marketable candidate. Potential certifications include certified applications professional, Cloudera certified professional: data scientist, EMC: data science associate and SAS certified predictive modeler using SAS Enterprise Miner 7. Search for positions such as Junior Data Analyst or Junior Data Scientist. System-specific training or certifications in data-related fields (e.g., business intelligence applications, relational database management systems, data visualization software, etc.) might help when looking for entry-level data science jobs.
The post How to become a Data Scientist of the 21st Century? appeared first on Analytics Insight.