HackerRank and HackerEarth Recruit provide Julia skills assessment tests online to help programmers, employers and recruiters demonstrate and assess programming skills, post and find jobs and connect.
According to HackerRank’s co-founder and CTO Harishankaran Karunanidhi, “We received a significant number of community requests to add Julia as part of our supported languages to solve HackerRank challenges. HackerRank users will be able to solve algorithmic, data structure and many other types of challenges using Julia as their preferred language.” To experience Julia on HackerRank, users can visit https://www.hackerrank.com/challenges/solve-me-first and select Julia.
Julia Computing CEO and Julia co-creator Viral Shah explains, “Julia programmers are highly sought after and command a significant earnings premium in the marketplace. Julia programmers are being recruited and hired to work in artificial intelligence, robotics, quantitative finance, high-frequency trading, precision medicine, genomics, aerospace and many other fields. We are excited that HackerRank and HackerEarth Recruit have added Julia to their skills assessment tests in order to help match Julia programmers, employers and recruiters.”
About Julia and Julia Computing
Julia is the fastest modern high performance open source computing language for data, analytics, algorithmic trading, machine learning and artificial intelligence. Julia combines the functionality and ease of use of Python, R, Matlab, SAS and Stata with the speed of C++ and Java. Julia delivers dramatic improvements in simplicity, speed, capacity and productivity. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. With more than 1.2 million downloads and +161% annual growth, Julia is one of the top programming languages developed on GitHub and adoption is growing rapidly in finance, insurance, energy, robotics, genomics, aerospace and many other fields.
Julia users, partners and employers hiring Julia programmers in 2017 include Amazon, Apple, BlackRock, Capital One, Citibank, Comcast, Disney, Facebook, Ford, Google, Grindr, IBM, Intel, KPMG, Microsoft, NASA, Oracle, PwC and Uber.
Julia is lightning fast. Julia is being used in production today and has generated speed improvements up to 1,000x for insurance model estimation and parallel supercomputing astronomical image analysis.
Julia provides unlimited scalability. Julia applications can be deployed on large clusters with a click of a button and can run parallel and distributed computing quickly and easily on tens of thousands of nodes.
Julia is easy to learn. Julia’s flexible syntax is familiar and comfortable for users of Python, R and Matlab.
Julia integrates well with existing code and platforms. Users of C, C++, Python, R and other languages can easily integrate their existing code into Julia.
Elegant code. Julia was built from the ground up for mathematical, scientific and statistical computing. It has advanced libraries that make programming simple and fast and dramatically reduce the number of lines of code required – in some cases, by 90% or more.
Julia solves the two language problem. Because Julia combines the ease of use and familiar syntax of Python, R and Matlab with the speed of C, C++ or Java, programmers no longer need to estimate models in one language and reproduce them in a faster production language. This saves time and reduces error and cost.
Julia Computing was founded in 2015 by the creators of the open source Julia language to develop products and provide support for businesses and researchers who use Julia.