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Digital Transformation with COVID-19

Spring 2020, much of the world is in a lock down. Economies are shut down and recovery will take a long time after coronavirus infection. Quarantine leads to a change in the operating mode for businesses, implications in team management and massive layoffs. With the spread of COVID-19, some companies demonstrated resilience, in particular, those for whom online was has been a  norm before. Can we see the current structural changes as  a path for a digital transformation? Or further development of AI. Great opportunity to take AI to the next level.  

AI and remote work

 As technology, AI and data science have already become a part of many work streams even in the industrial applications.

 In such circumstances, the main task of employers is to reproduce and debug all the work processes in the new conditions as if nothing has changed radically. The employees, in turn, need to make sure that the inevitable distractions at home do not interfere too much with the main tasks. New norm.

What is next?

As already noted by one authoritative publication, life in post-lockdown will be different. The current situation in production has shown how vulnerable people are: many factories have to be closed because workers must be self-isolated. This dependence on human resources has shown manufacturers the need to automate production.

The fields of robotics and artificial intelligence require more workers to keep up with the recent surge in demand, and as the use of machines increases across all industries, some low-skill jobs will be lost. However, they will be replaced by new more highly skilled positions. New places are being opened that requires training, experience, and a willingness to work with machines, not against them.

AI can create more jobs than it can replace.

Data Science and AI jobs

Many companies offer a large number of jobs related to a machine learning. Check this out.

Job: Data Scientist.

Description: Data Science is a field of research that studies the problems of analyzing, processing, and presenting data in digital form. Data Scientist is an expert in analytical data who has technical skills to solve complex problems, as well as a curiosity that helps set these tasks. They are part mathematicians, part computer scientists, and part trend spotters.

For example: KēlaHealth offers a data specialist workplace. As an employee of this organization, you will work with large health data sets that include complex data extraction, programming, and analytical modeling to support applications. You will develop and conduct experiments using machine learning methods and other statistical approaches to develop and improve algorithms that can be used in production.

These requirements can be met from home, provided that certain equipment is available.

Job: ML Engineer.

Description: Machine Learning is an extensive division of artificial intelligence that studies methods for building models that can learn, and algorithms for building and learning them. The Machine Learning Engineer position is more “technical”. In other words, ML Engineer has more in common with classic Software Engineering than Data Scientist.

Standard ML Engineer tasks are generally similar to Data Scientist. You also need to be able to work with data, experiment with various Machine Learning algorithms that will solve the problem, create prototypes and ready-made solutions.

For example: Imvaria offers such a position. Responsibilities include: building AI models for medical data; machine learning development; software development; junior machine learning engineers mentor. 

Job: Software Engineer.

Description: Software Engineer is a specialist who develops software using engineering principles and relies on fundamental knowledge of Computer science.

For example: Drchrono is looking for an employee for this position. The employee’s duties are to manage and improve the billing tool; introducing innovations and improvements to the billing product with a focus on developing features, configuring clients, and refactoring code; testing programs that ensure operation and troubleshooting.

There are many diferent platforms which suggest not only work but also studying courses. You can do them during lockdown and become a better specialist in AI and machine learning. Learn more here.  

TaQadam Data Team

Our company TaQadam also has opportunities for AI remote work. Here are a few possible work tasks.

Data Annotator (images)

Data Scientist (datasets and pipelines)

Data Analyst (interpretation)

Image annotation is one of the most important tasks performed in our company. Employees at AI remote work can perform annotating from home using their own PC or our smartphone app.

When creating machine learning, an employee is required who will create pipelines for training, testing and validation cycles. Good understanding of the Machine Learning principles is required to support our clients. 

Analyst’s task is to analyze the dataset, to create relevant conclusions for analytics. For example, a dataset containing the number of trucks at the warehouse. The analyst, in turn, gives interpretation on economic activity. For example, if the number decreases during the productive hours sharply, it means that the site is to close?

Managed Teams

In our company, we work exclusively with managed teams. This approach means that we have our own working team, whose members live in different parts of the world. This type of work differs from using freelancers/crowdsourcing. The team is permanent and formed for each client, each employee performs certain functions and works in TaQadam for the long term. Therefore, managed teams provide a certain stability in the brand’s operation.