There are various practical data science skills for applicants to apply for FAANG companies, here are the top 10.

Data science as one of the greatest jobs in the contemporary technology market is considered a highly technical role. Data science is the cutting-edge technology that is ruling a wide range of sectors and companies today. Data science skills are crucial in this age of AI, big data, and automation. FAANG companies are looking for skilled professionals who can manage the ever-increasing amount of data generated by their operations. There are various practical data science skills for applicants to apply for FAANG companies. This article lists the top 10 data science skills that will get you a US$1M FAANG job.

Statistics and Mathematics

Statistics, probability, and mathematics are the premise of Data Science, Artificial Intelligence, and Machine Learning. One can't plan hearty ML calculations without having solid groundwork in these three fields. It is inordinately difficult to extricate significant bits of knowledge from unstructured informational indexes. Measurement is an unquestionable requirement to do information arrangement and investigation.

Cloud Computing

Practically every one of the significant ventures is moving from in-house servers to some type of cloud computing. Further, the applications are created as a bunch of free microservices that are conveyed and run on the cloud. Cloud computing permits associations to scale their IT system as per the requests and save both activity cost and capital speculation.

Explainable AI

Many machine learning algorithms were considered 'block boxes' for a long time because it wasn't clear how these models derived their predictions based on their respective inputs. SHAP and LIME are two techniques that tell you not only the feature importance for each feature but also the impact on the model output, similar to the coefficients in a linear regression equation.

Data Visualization

Data visualization is the key to effectively communicating messages and getting buy-in for proposed solutions. Understanding how to break down complex data into smaller pieces and using a variety of visual aids is a skill that data science professionals should be proficient in. They should be able to create charts, graphs, and other such things to help enable other data science employees to find out errors while presenting and rectifying them.

Multivariate Calculus & Linear Algebra

Most machine learning and invariably data science models are built with several predictors or unknown variables. Knowledge of multivariate calculus is significant for building a machine learning model. Here are some of the topics of math you can be familiar with to work in Data Science: Derivatives and gradients, Step function, Sigmoid function, Logit function, and ReLU (Rectified Linear Unit) function, etc.

Leverage Self-Service Analytics Platforms

C-suite leaders should not only gain insights on utilizing such advanced technologies but also understand the challenges involved in utilizing them. They have to possess the basic knowledge of market solutions, know and apply the best practices and techniques and have the ability to share results through self-service dashboards or applications.

Data Wrangling

Often the data a business acquires or receives is not ready for modeling. It is, therefore, imperative to understand and know how to deal with the imperfections in data. Data Wrangling is the process where you prepare your data for further analysis; transforming and mapping raw data from one form to another to prepare the data for insights. This is the most important data science skill that one must have.

Database Management

With heaps and large chunks of data to work on, it is quintessential that a data scientist knows how to manage that data. Database Management quintessentially consists of a group of programs that can edit, index, and manipulate the database. The DBMS accepts a request made for data from an application and instructs the OS to provide specific required data.

Neural Network Architectures

Neural networks make up part of the deep learning process and are inspired by the structure of the human brain. They are complex structures created from artificial neurons that can process multiple inputs and produce a singular output. Understanding this architecture is essential for deep learning. It is one of the best data Science skills one must have to enter the big tech world.

Critical Thinking

With critical thinking, data scientists can objectively analyze questions, hypotheses, and results and understand what resources are critical to solving a problem. They can also look at problems from a different perspective. Critical thinking is a valuable skill that easily transfers to any profession.

More Trending Stories