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How to Coop up with Evolving Job Roles in the Deep Tech Industry

Deep tech is gaining popularity because it provides smart solutions to complex problems like climate change, healthcare disparities, cybersecurity, and inclusive societies. The industry is growing rapidly due to advanced technological innovations, particularly in engineering. Numerous new startups are emerging, each offering unique solutions to existing challenges. Job roles in the field are also changing. Some positions focus on creating platforms for deep tech success, such as ChatGPT, while others aim to digitally transform industries by leveraging technologies like ChatGPT.

See the picture below, “My dear, here we must run as fast as we can, just to stay in place. And if you wish to go anywhere you must run twice as fast as that!”

Future Year 2063:What job roles do you expect in this world? 

Here are some of the top jobs in the field of CS/AI/ML/Data Science:

1. Quantum Computing Engineer: These professionals utilize quantum mechanics to enhance computational power.
2. AI Ethicist: They ensure that technological advancements align with our values and societal well-being.
3. Genomic Data Scientist: They explore genetics to unlock personalized medicine and scientific discoveries.
4. Robotics Architect: They shape automation and intelligent machines to revolutionize industries and augment human capabilities.
5. Clean Energy Engineer: They develop innovative solutions to combat climate change by harnessing renewable energy.
6. Cybersecurity Analyst: They strengthen security measures and protect against cyber attacks.

In the meantime, say till 2043 the top jobs will be related to Data: Addressing the challenges faced by different industries requires a significant amount of data. Therefore, the top jobs in this field involve working with data in various forms, such as data engineering, data analysis, data science, and data visualization. However, data alone is not sufficient; effective storage and utilization require platforms, cloud systems, distributed systems, or hyper ledger systems. In the coming decade, AI will continue to be a major focus, leading to new job opportunities for professionals who can ethically and responsibly work with data. Additionally, there will be an increased demand for UX designers, front-end and back-end developers, and web developers.

In the rapidly changing world of deep tech, continuous upskilling and a strong foundation in design and programming are essential, regardless of the programming language used. Being a proficient problem solver and having the right mindset is crucial for mastering any technology. Adaptability to the evolving landscape is key to success. Building a solid foundation and nurturing meta-skills enable professionals to quickly learn any technology. For instance, critical thinking and problem-solving abilities can facilitate learning skills like AI/ML, data science, cloud computing, distributed systems, systems design, SAP, blockchain, and IoT. As for programming languages, knowledge of Object-Oriented Programming (OOPs) can facilitate learning languages like Python, Java, Angular, Scala, and others.

With numerous career paths available, it is important to stay focused and have clarity about personal interests and goals. Career transitions and staying updated with skills and technologies take time, so it’s advisable to take small steps. Instead of immediately investing a significant amount of money in AI or blockchain courses, it’s better to start with free courses available on the internet. Companies like Google, Amazon, Microsoft, and reputable universities offer freely accessible blogs and videos. This allows individuals to assess their interests and determine if the subject truly appeals to them. Once confirmed, they can explore reasonably priced courses on platforms like Coursera or LinkedIn Learning before enrolling in more expensive options. Additionally, pursuing a degree program in the relevant field is also a viable option.

Finally, practical application is crucial for comprehensive learning. Writing blogs and working on practical projects involving design and coding are important steps. By following this systematic approach, transitioning to a new role, and changing domains or industries becomes much easier with relevant hands-on knowledge.

Regardless of the job, important skills for success in deep tech include adaptability, proficiency in data analysis, machine learning, and data visualization. Understanding algorithms, optimization, cryptography, and the ability to collaborate in interdisciplinary teams will continue to be highly valuable. Finally, be ready for change and upskill every day. I fondly quote the lines from ‘Alice in Wonderland’, that is, “My dear, here we must run as fast as we can, just to stay in place. And if you wish to go anywhere you must run twice as fast as that”.