Today’s Hottest Computer Science Jobs
Computer science is a vast field with many attractive and highly lucrative job opportunities. There are some roles that have recently become popular because employers are demanding qualified employees in larger numbers. In this article, I offer an overview of some of the most rewarding and in-demand computer science jobs today.
Good software is incredibly hard to write, and many non-coders underestimate the complexity involved in a software system. Software engineers are the professionals responsible for conceptualising and designing beautifully designed modular code that powers everything from your smart fridge to the Internet itself. Given the proliferation of technology and its pervasiveness in everyday life, software engineering is a job that’s not going anywhere anytime soon. Starting annual salaries in Silicon Valley’s top companies, such as Google, Facebook and Slack are ~$100,000, with considerable stock options and other benefits to boot.
The job of a Data scientist is to look at data – whether structured or unstructured, limited or vast, complete or incomplete – in various contexts, and provide insights that help a company improve sales, revenues, profitability or other performance metrics.
The terms Data analyst and Data scientist are sometimes used interchangeably. While there is overlap in the work of both, there are also considerable differences. A data analyst collects, processes and analyses data using a standard statistical toolkit. A data scientist, however, does that and more by employing techniques from machine learning and predictive modelling to create, process and validate a framework that can be used to forecast the probability of future outcomes. Top tech and financial firms such as JP Morgan, LinkedIn, and Fidelity Investments employ data scientists and pay on average ~$115,000 along with stocks and other benefits.
Machine Learning Engineering
Machine learning is a form of artificial intelligence (AI) that uses statistical methods to enable computer systems to “learn” from data, without being explicitly programmed. In today’s world of on-demand and customisable solutions, machine learning has practically limitless applications. From Netflix’s show recommendations to predicting which ad you are most likely to click on, machine learning models are ubiquitous. As a result, there is tremendous demand for engineers who specialise in machine learning. Again, all top tech companies including Google, Facebook, Quora and Netflix have machine learning engineers with lucrative offers averaging around ~$115,000 with the usual options and benefits. The field is only going to get more attractive with increased opportunities and improved technologies.
There’s a set of features that users want in a product or service, and then there is a set of all that can be realistically built with constrained resources. A product manager’s job is to find the intersection between the two sets. For example, Google, and Uber take different approaches to the product management (PM) role, but most require PM’s to be able to work at the intersection of software technology, product, marketing and user demand. Companies with interesting PM roles include Google, Lyft, Yelp, Salesforce and Facebook with salaries going as high as $180,000 and averaging around $100,000.
Ayush Sharma is a guest blogger for The Red Pen and final year computer science student at Massachusetts Institute of Technology (MIT)