Deep tech companies require certain skills in their workforce. Due to the long R&D time required by deep tech, skilled workers can shorten project duration and greatly reduce project cost, not to mention improve the quality of deliverables to the stakeholder.
Also known as hard tech, deep tech is a classification of a company, especially a startup, with the goal of solving tough technological or engineering problems.
Research and development take much longer than usual, but long-term market risk is typically low because of the clear value of the eventual end product. Business models for these emerging technologies must take a novel approach to fundraising.
Examples of deep tech include artificial intelligence, blockchain, web3, biotechnology, robotics, quantum computing, photonics, and advanced manufacturing. Deep tech is contrasted against shallow tech, such as apps or websites, which take less time to develop.
More and more organizations are investing in deep tech and deep tech skills. For instance, the European Institute of Innovation and Technology (EIT) just launched The Deep Tech Talent Initiative at 2022’s INNOVEIT WEEKS event series, “inviting partners to join its efforts to skill one million people within deep tech fields over the coming years.”
Now that organizations and governments are investing more in deep tech entrepreneurship than ever before, it’s important to hire the best freelancers with proven skill sets. Become a client of MVP Match — we match businesses with vetted freelancers of the highest caliber.
What are the top 10 skills for deep tech? If workers want to increase their chances of landing a job in deep tech, below are the top 10 skills they should be fostering via higher education providers or hands-on experience:
Big data analysis
Internet of things
Blockchain is famously the building block of Bitcoin and other cryptocurrency, but blockchain’s applications are nearly endless in multiple sectors.
Also known as Web 3.0, Web3 is a blockchain-based model for the worldwide web. Mostly theoretical in 2023, Web3 skills are still rare, but the demand for knowledge of this new technology will sharply rise over the coming decade.
Web 1.0 was the earliest version of the Internet — mostly just static web pages — emerging from the Defense Advanced Research Projects Agency (DARPA). Web 2.0 represents more user-generated content and ease of use for the average person (think: social media and e-commerce websites).
In theory, Web 3.0 will utilize the blockchain, decentralization, and crypto token-based economies. Proponents claim it is the next evolution of the Internet.
With big companies and entrepreneurs announcing partnerships with blockchain and decentralization companies, Web3 is here to stay, and it’ll keep growing. Web3 skills are rare, but Web3 workers will give you a competitive edge.
Machine Learning & Artificial Intelligence
ML and AI have become ubiquitous buzzwords for a reason. Machine learning (ML) and artificial intelligence (AI) promise massive leaps in utility and efficiency, but they require a lot of research and development.
Companies can save themselves time and money by hiring workers or freelancers who already have ML/AI skills.
Demand for workers with this skill set is constantly increasing, as huge companies like Google, Amazon, Meta, and Microsoft search for more and more ML/AI specialists.
ML and AI skills are especially needed in the sectors of:
In this age of big data, companies will always need more efficient data analysis algorithms and digital transition of data. Deep tech continues to create better data analysis tools for various sectors, including healthcare, manufacturing, media, finance, renewable energy, and even sports.
Deep tech workers should possess a strong understanding of data science and analysis. A STEM background is a huge plus towards understanding the potentials of data science, especially if a worker wants to become a project manager in deep tech.
The applications of data science are limitless, and this deep tech field will continue to grow into the future. The U.S. government predicts a sizable increase by 2026 in companies requiring data science skills.
The Internet of Things (IoT) refers to networks of physical devices, as well as the technology which allows communication between these devices and the cloud. High-quality IoT increases efficiency of communication and data storage, which most companies would benefit from.
Therefore, deep tech startups will benefit from a skilled labor force that understands cutting edge IoT and how it is implemented in applicable industries.
This multi-trillion dollar industry will continue to grow as heaps of data continue to be stored in the cloud. Cybersecurity and latency reduction are two vital areas of IoT that deep tech might want to invest time and resources in.
Cloud & Edge Computing
Adjacent to IoT, cloud and edge computing are important and versatile tech skills for deep tech workforces.
Cloud storage has overtaken the daily lives of most consumers in 2023, and its applications will only increase. Edge computing brings cloud data sources closer to the applications which use that data, decreasing latency and bandwidth usage.
Nearly all companies depend on cloud ecosystem solutions, and deep tech would benefit from workers with edge computing talents.
Robotics can be useful in most industries, or at least will be in the coming years. From healthcare to manufacturing, robotics can make companies more efficient and more profitable.
Workers and freelancers who already possess skills in robotics are valuable to deep tech companies.
Robotics is an important field in deep tech, and its applications are far-reaching — from transportation to manufacturing to climate change science. Build a workforce with robotics skills, and you’re setting your organization up for success.
Quantum computing might be the next deep tech innovation which will revolutionize society across the globe.
Until we get there, deep tech needs more workers with experience or education in quantum computing.
Traditional computer transistors can currently get thinner than a strand of DNA — 0.34 nanometers wide. A silicon atom is 0.2 nanometers wide, which is the smallest that silicon transistors can get. The limit of traditional computer advancement is fast approaching, and that’s where quantum computing will become absolutely necessary.
Theoretically, quantum computers have far more advanced processing power than conventional computers. They also will not be limited by the width of a silicon atom. Quantum technology is useful for virtually every industry on the planet.
Quantum computing may be in its infancy, but in just a few years, quantum tech will disrupt how we do everything concerning a computer. Deep tech companies would benefit from staying ahead of that curve.
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