Best 7 Data Science Skills You Should Not Miss By James Tredwell on August 27, 2019 Leveraging big data as an insight-generating engine has driven the demand for data scientists across all industry verticals. As the demand for data scientists advances, it extends an enticing career path for students as well as professionals. While a fruitful career choice, it requires a deep understanding of the business world and a set of critical traits in order to become successful data scientists in today’s competitive marketplace. Following are some of the skills that companies look out for in a data scientist:- Critical Thinking Being a critical thinker is one of the most imperative skills as it allows data scientists to perform objective analysis on the facts of a particular subject matter or problems, before offering the right solution. Expertise in Mathematics Data scientists engage with clients who are looking to develop operational and financial models for their companies, and this involves the analysis of a large amount of data. They leverage their expertise in math to formulate accurate statistical models that further serve as the basis for developing important strategies and facilitating approvals on decisions. Proficiency in Coding Data Science Course Using R, Excel, Python enables data scientists to write code and efficiently deal with complex tasks associated with coding. To be a successful data scientist, one must have programming skills that include computational aspects (cloud computing, unstructured data, etc.) and statistical aspects (regression optimization, clustering, random forests, etc). Understanding of AI, Machine Learning, and Deep Learning Owing to advanced connectivity, computing power, and collection of enormous data, companies are increasingly leveraging technologies like AI, machine learning, and deep learning. To be a successful data scientist, one must have extensive knowledge of these technologies and possess the ability to identify which technology to apply in order to avail the most effective results. Comprehending Data Architecture From interpretation to the decision-making process, it is important that data scientists understand how the data is being used. Not understanding the data architecture can seriously impact the interpretations that might result in businesses making inaccurate decisions. Good Business Intuitions Data scientists must look at the business world from various perspectives to understand what needs to be done, and consecutively build strategies in achieving the end result. Therefore, good business intuition and a problem-solving approach are the two common skills that every company looks out for when hiring a data scientist. Ability to Analyze Risk A skilled data scientist should be able to understand the concepts of business risk analysis, how systems engineering works and needs to make improvements in the existing process. Risk analysis in the initial stages of the model development allows businesses to mitigate any unforeseen risks and make profitable decisions with care. Data science is a multi-disciplinary domain that requires professionals to hold a strong knowledge base (through data science course) and domain-specific expertise. According to a recent study by IBM, the demand for data scientists will increase by 20% by 2020. Above are some of the imperative skills that data scientists must possess in order to carve a successful career path in the corporate domain.