Job requirements change constantly. A company seeking a data scientist in 2020 will likely post a different job description than one they posted a year ago, including broader data science expertise. As expectations and desired deliverables shift across industries, oftentimes the tools needed to meet these demands change.
We scoured hundreds of data science job descriptions and found out the most common fields of expertise that employers are looking for. In this article, we will provide a high-level overview of broad expertise. In future articles, we will look at the more specific soft and hard-technical skills that companies are looking for.
Overall job demand on the rise
As seen in chart #1, the overall demand for data science jobs is on the rise. Companies are actively seeking data scientists of all levels and will likely continue doing so for quite some time. The rise in actively seeking data scientists could possibly correlate with many organizations looking to reframe some of their initiatives given the changing dynamics due to COVID-19.
Machine learning is still king
Given the clear and obvious growth of machine learning as a field, it shouldn’t be a surprise that machine learning expertise is still the most sought-after skill in data science. Popular and open-source frameworks, libraries, and tools make machine learning a realistic approach for many organizations to tackle AI, as opposed to more granular, expensive, or resource-intensive approaches like deep learning. Knowing hot topics in machine learning is a massive difference-maker.
Engineering is needed to make it happen
Most companies aren’t exactly looking for theoretical data science – they want tangible products and workflows to make magic happen. As such, data science engineering is needed to turn models from pilots to production and to see the automation or analyses take place. Picking up the skills to create these products is paramount to your success.
A breakdown of the most sought-after skills from job descriptions. Source: getaiplus.com
Statistics are still incredibly important
Knowing math and statistics are the fundamentals of data science expertise. Whether it’s through analysis or automation, having expertise in Bayesian statistics or another field will give you a strong foundation to create models from the ground up.
Companies are still looking for data analysis
While many businesses are looking for automation or ML workflows, there’s still a lot to be gained from data analysis and finding insights from existing data. Any good organization would want to identify trends in their data and to make quick decisions without taking a deep dive into a machine learning process.
Programming is a requirement
Any good website, process, or statistical analysis requires good programming skills, and the modern data scientist is expected to know how to program as well. Plus, there are plenty of overlapping languages like SQL and Python, or environments like Jupyter.
Big data plays a big role
You can’t go anywhere without hearing about big data anymore, especially with larger companies (which often hire many data scientists). In order to maintain these massive data sets, a data scientist should know how to develop at scale and how to maintain & work with a large database.
Communication is key
Data is tricky, and not everyone can easily understand it, especially other stakeholders like the marketing team or executives. As such, a good data scientist should have clear communication skills like data visualization and storytelling, and be able to clearly describe their requirements, methodology, and results. There are countless approaches to learning data visualization across a variety of channels & mediums.
Learn this data science expertise and more skills at ODSC
Above, we listed off a number of complex topics that can set you apart in your search for a career in data science in 2020. By engaging with ODSC’s numerous training opportunities, you can gain these skills and get ahead.
Skills for all levels of expertise
ODSC events, such as ODSC West coming up October 27-30, offer unparalleled options for growing your skillset regardless of your current level. From introductions to machine learning to advanced, cutting-edge research into novel frameworks, there’s something for everyone at an ODSC event.
All topics and disciplines under the AI umbrella
Being a data scientist doesn’t just mean being an expert in machine learning. ODSC events and AI+ training programs cover every aspect of data science, from machine and deep learning to NLP and data visualization, there’s something for every aspiring data scientist.
Learn both timeless and in-demand skills
Just as with any career, you’ll need to know both timeless skills and what’s new. For data science, this means knowing the foundations of R and/or Python, plus knowing all of the latest tools, frameworks, and libraries available. We offer workshops on the skills that employers are looking for right now, such as data engineering, data science at scale, ML workflows and MLOps, and more.
Attend bootcamps to start strong
Especially beneficial to those new to data science, our data science bootcamps offer a strong foundation that covers everything you need to get started in your career. These mini-bootcamps will turn you from a beginning data scientist into an expert in less than a week – and that’s a lot faster than any degree will get you. Your resume will explode with new skills that employers will see and they will take notice.
Live and on-demand training year-round to gain data science expertise
We also offer a series of live and on-demand training options through our AI+ Training platform. In these training options, you’ll learn the hard, technical skills that you need to get ahead. In the coming months, we have offerings in novel machine learning techniques, data visualization, gradient boosting, programming with Python, and more to be announced.