Clean Tech and Data Science Trends In The Age of Covid: Part III

So far, we’ve been looking at the trends in the clean technology and data science sector during the pandemic in terms of companies’ requirements, startup activity and acceleration of existing trends in automation, robotics and artificial intelligence. Today, we’ll wrap up our series with a look at how jobs in this sector are holding up and the skills that are increasingly in demand.

 

First, how has hiring in the sector been impacted? Like many sectors, hiring in the clean technology and data science sector has slowed as companies and organizations evaluate their status and determine what will be needed in the year ahead. Hiring in many traditional roles in organizations and companies (e.g. environmental consultants, power plant engineers, wastewater treatment scientists, city sustainability officers) has been put on pause or eliminated at this time. These companies are essential organizations and are open, but they are typically operating with a skeleton staff and are still evaluating the financial impact of the economic downturn before hiring.

 

However, we are seeing significant activity in hiring in certain sectors and companies. The tech companies are still hiring - Microsoft, Google, Facebook, and Amazon being the primary ones. These companies are still searching for people for their sustainability efforts and these are usually roles that require a significant level of data science in addition to degrees and/or experience in the sustainability and clean technology sector. 

 

There’s also hiring in several startups that working at the intersection of clean technology and data science. These are startups that have already a significant presence in the field and revenue from customers - so they’re still looking to fill existing open positions, even if their expansion plans have slowed. New startups are looking more shaky as the availability of venture funding is looking uncertain, but established startups that have a good product-market fit are promising places to find jobs and build careers, even at this time. Farmers Business Network, Autogrid, Orbital Insights, Planet, and Indigo Agriculture are among the startups that are relatively well funded and are still posting job openings. 

 

Additionally, there’s an uptick in jobs in several utility companies and large corporations in water, energy and agriculture. Climate Corporation, Sentient Energy, municipal water utilities in different cities have posted openings looking for people who have experience in the clean tech sector in question (e.g. water or energy) and can also do things like evaluate and model sensor data remotely, build predictive models and create analytical reports and dashboards that executives and operators can use for remote operations.

 

So, there are several silver linings in the job market right now. The kind of work and the kind of skills that are being sought are different from the ones that a traditional education confers, but jobs are there and there are careers to be built by those who are looking to expand their skill sets.

 

So, what kind of skills are most in demand right now?

 

Right now, a combination of data science and clean technology skills is one of the most sought after skill set, especially where you have a strong background in a clean technology sector (water, agriculture, climate, energy and so on). As we had discussed in the first post in this series, remote operations and remote monitoring has suddenly moved from a nice to have to a must-have for many utility companies in energy, water, and waste sectors. It’s difficult to work remotely without having sufficient data and being able to compensate for cases when data is scarce or difficult to obtain. So, people who can identify anomalies, predict trends, model and understand what the data actually means and where it can be used are now essential. 

 

Probably the most immediately important skill set lies in obtaining, visualizing data and identifying anomalies. This is where tools like Tableau, QGIS, ArcGIS are useful because they can help make sense of streams of data immediately. Understanding the sector, being able to make sense of the data and building useful analyses and dashboards are among the most important skills right now.

 

The second set of skills relates to the ability to code and build models that can identify anomalies, spatial and temporal patterns in data. And in some cases, build relatively simple predictive models for spatial and temporal trends. These tasks can usually be accomplished using Python or R alone or in combination with the earlier visualization tools. Remote sensing, spatial statistics, time series analyses - these are all highly sought after skills right now.

 

The third level of skills are a function of the depth of subject matter expertise and machine learning expertise. This is where companies and organizations are looking for leaders and senior scientists and engineers who can drill down into the problems, create novel models or use existing algorithms and models to do novel analyses, and create and identify new business opportunities. This is where people who have been working in the field for a long time and have a solid working knowledge of machine learning and statistics are in demand.

 

One of the most overlooked skill sets until now has been the ability to translate between data science specialists and clean technology experts. In many ways, professionals in both fields have very different view points and someone who can understand both fields, explain them to each other and and translate the issues is invaluable!

 

In summary, changes are coming to the clean technology and data science sector, but those who can adapt to the increased use of automation, artificial intelligence and remote operations as well as add to their skill sets are likely to take advantage of these changes and be successful.