As more and more jobs are available in the fields of data science and artificial intelligence, industry experts have put forward some suggestions for those who want to make career planning in these two fields.

It is certain that there are a large number of vacancies in the positions of data scientists and artificial intelligence professionals, which will continue to grow rapidly in the coming year. To help those in the industry who apply for these positions, the following will be introduced:

• what skills do data science students / professionals want to learn most? How does this match the market demand?

• what are the potential career paths for students / professionals who are developing their data science and AI skills?

• how can candidates better prepare for interviews for data scientist positions?

• why is it important for business and computer science majors to collaborate on machine learning algorithms?

• what are the general recommendations for students or professionals who wish to apply for a career in data science or artificial intelligence?

In order to deeply understand the career planning of professionals in artificial intelligence and data science, Ted kwartler, vice president of trusted artificial intelligence of datarobot, a machine learning platform manufacturer, expounded and analyzed this. Kwartler is also an adjunct professor of business data mining at Harvard University.

Kwartler said, “data scientists are arguably one of the most popular disciplines in Harvard University in the past decade. There is a large shortage of jobs. I realize this, and so are my students. Moreover, many enterprises are trying to fill this vacancy by training their employees, and many employees are very interested in it because they can get higher salaries.

A friend of mine, who works in a large technology company, received 1% of the company’s profits in the enterprise acquisition, and his income is absolutely impressive. Those who want to take this career path may ask, ‘how do I enter this industry and build my career?’ First of all, don’t pay too much attention to salary, but regard its field as a happy land. “

What skills do college students and professionals want to learn about data science and artificial intelligence? How do these skills match market demand?

Kwartler said, “many students are very interested in building artificial intelligence models. For example, they like to build deep neural networks for image recognition. They are very active in learning mathematical knowledge, writing code and building models. This is an exciting process, and it is also a process of real dedication… In fact, building models takes a lot of time.

The model I mentioned does not necessarily use big data, but ‘big enough’ data. However, there is a gap between theory and practice. Therefore, these students may spend six months to build a perfect model and optimize it to the sixth decimal place.

However, if we only try to build a customer preference model and provide some new services for the call center, but the business itself does not need these functions, there will be a gap between the actually needed functions and exciting technologies.

When I worked in Liberty Mutual, I was a member of a machine learning research team. Our team spent three to six months to acquire data, sort out data, optimize models, and then spent three to six months to cooperate with the IT department to complete the research. Such work is very heavy. Many data scientists don’t even like to work on the data part because they don’t understand the business and use cases. “

When people begin to plan their careers in the field of data science and artificial intelligence, what career paths are really meaningful to them? What is a really practical career path?

Kwartler said: “The career of data scientist is very interesting. I have an MBA degree and am completely self-taught. Some competent and motivated business analysts of datarobot are citizen data scientists. We hope they will become professional data scientists. This can be done through training or software. The interesting thing about their career path is that they need a lot of time to learn business and understand Build the story behind the model, because these start from the initial stage.

A different career path is like being a mathematician or an expert with a doctorate in astrophysics. They can definitely build excellent models. For them, the challenge is how to expand more in the business.

The third is the software engineer who wants to learn modeling. Now, the demand for machine learning engineers is growing. They have rich experience in programming and have a sufficient understanding of computer science and put them into production.

Therefore, I think these are three very important career paths, so professionals have a variety of ways to achieve their goals. In addition, I think we need experienced managers who know how to work with these technicians.

Technicians can discuss with such managers about the fluency of data and the geospatial data being submitted by autonomous vehicle. They are connected through API and are using deep neural network image recognition. When technicians are unable to make strategies, managers need to have some basic knowledge of certain technologies and make decisions. Therefore, I think managers can expand the scale and ensure the rapid development of their business. “

In terms of interview skills, what suggestions would you give to help candidates obtain AI jobs? How can candidates be better prepared and present themselves?

Kwartler said, “in fact, I hope every candidate knows that it has to do with perseverance. If the candidate doesn’t get the job he wants, don’t lose heart. He must persevere to improve his skills and level. In fact, I have applied for 83 companies.

The first thing I want to say is that candidates should consider their own level, what knowledge and skills they have, and what kind of talents the enterprise needs. The next stage is usually when the candidate knows how to better communicate with the recruiter. Recruiters need candidates with technical depth.

This is a balancing act because they want to know if the candidate is competent. Candidates can show some of their talents. But in general, because it professionals are usually very frank, candidates should also be frank with themselves.

I think data science is a team activity. That is, they need to communicate constantly and require the completion of best practices. This field is so diverse that no one knows how to deal with various problems. Therefore, it is often necessary to interact with others to obtain best practices and experience in technology, not to mention how to put the built model into production. So there is still a need for interpersonal communication skills and some good topics, such as building the best possible model. “

What is your general advice for students or professionals who wish to apply for a career in data science or artificial intelligence?

Kwartler said, “people may see that there are many jobs available in these two industries. If you know these jobs, you can put candidates on the path of data science. So don’t limit your choices. As far as a university degree is concerned, it is just a stepping stone to open the door to the industry.

However, people will find that people with datacamp or bootcamp certification have achieved a lot of success because there is a real market demand there. So for those college students who are interested in these careers, they need to find a research project that can be more enthusiastic. Because there will be more motivation to learn, such as how to collect statistical data of basketball comparison through the Internet and how to download stock data. Encounter obstacles, and have the ability and motivation to overcome this obstacle. And spend a lot of time on technical forums and stack overflow. The learning results are obtained through continuous practice. So I don’t think a college degree is really that important.

College education can help college students open the door to the industry and help them get internships. Graduates with a degree from a famous university do not worry about having no job opportunities, but having an industry certification certificate can provide greater help. “

Responsible editor: CT

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