More and more companies are looking for talented analysts to process and interpret the data they produce. But what does data science mean in the energy sector? Safety, economy, and connectivity for a start!
Data analytics and machine learning can help the energy industry to:
Increase safety and prevent accidents.
Reduce operational costs.
Optimise production processes.
That is the reason why companies are seeking a more connected workplace.
Technology can be used to predict the maintenance requirements for field equipment, for example. This proactive action enabled by data science reduces downtime and saves money. In terms of safety, many disasters are prevented through better information every year.
Most companies in the energy sector have invested in digital transformation to help them grow their businesses. And there is no way back. Data science, artificial intelligence, and automation are here to stay.
Do you have the data talent in place to stay competitive?
How is data science transforming energy?
All the sectors in the energy and utilities industry benefit from technologies and big data.
Utility companies can use data analytics to identify energy consumption and energy saving to manage power outages, figure out peak times and to set energy pricing.
Oil & Gas firms can use data science to help drive refinery, distribution processes, and adjust to market demands in real time.
Clean energy companies can use data for smart grid management and regulation. Machine learning algorithms can also be used for weather prediction and maximising efficiency of renewable energy sources such as wind and solar power.
"No sector is immune, and there are plenty of red flags around the entire energy industry’s ability to build a pipeline of qualified young people willing to join and remain in the industry.
As much as the workforce has embraced technology, it believes that securing the right people is the most important way to build resilience into the business. To that end, current employees want more training and mentorship."
What data science skills are in demand?
Data science is a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract insights from structured and unstructured data.
Data scientists are skilled in math and statistics, databases and programming languages. Premium data scientists have domain knowledge and understand how businesses work enough to create solutions for it.
They are not just analytical - they can explain the story behind the numbers
Job descriptions for a data scientist often look for experience with:
Algorithms and data structures.
Programming languages (e.g. Python, R, SQL).
Machine learning libraries (e.g. SciKitLearn).
Data visualisation (using a tool like Tableau/PowerBI or a Python library like MatPlotLib).
Communication (both written and verbal - to share data findings).
Domain knowledge (in the energy sector you may see reservoir engineers or geologists transition into data science).
What is the average salary for a data scientist?
Data scientists are in high demand around the world. If you don’t want to be tied down to one country, working as a data scientist can offer you the freedom and flexibility that you are looking for.
Digital transformation is now so important that there aren’t enough experts to go around.
The need for data science specialists has grown fast in such a short space of time. It’s becoming exponentially harder to fill roles, train new staff and build a workforce that both understands digital and the unique demands of the energy industry.
If you are looking for data scientists, Airswift can help you.
We already have access to those networks and will source the best data specialist for your team. With over 60 offices worldwide, 800 employees, and 7,000 contractors, Airswift is the agency of choice for world-leading energy businesses. Grow your workforce with us!