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Digital Skills

At this point, most of us tech people know we need some data science & machine learning skills in order to survive and thrive. But with so much buzz around these technologies, it is easy to lose track of what’s really important.

I see a lot of people running after the hype, trying to acquire lots of me-too skills without due diligence. As a result, the mismatch between acquired and required skills continues to grow.

Amid this overwhelming mess, knowing what trends are currently shaping the data science and machine learning landscape can help you be prudent about identifying the right skills where you need to invest your time and efforts.

So, let’s see 5 such key data science and machine learning career trends for 2019 that will help you build a future-proof career.

1. Companies Want Specialization

‘Data Scientist’ and ‘Machine Learning Engineer’ are fascinating job titles, but they are incomplete. Today, the industry has matured and companies are looking for specializations within these fields. For instance, here is a glimpse of all the data roles at Netflix.

data science machine learning career trends 2019 specialization

Besides, most AI startups operate in niches; therefore, require skills specific to that niche. For example, if a company is building an NLP solution, instead of posting a job vacancy for ‘machine learning engineers’ it would look for ‘NLP engineers’. In fact, if you look it up on LinkedIn, you will see every machine learning or data science job vacancy with some sort of specialization with it.

2. The Demand of Data Engineers Rises

There is an oft-cited LinkedIn survey that states that in 2018, the demand for data engineers exceeds the demand for data scientists. Data engineers are responsible for developing software components of analytics applications. They collect and store data and do real-time processing to ensure uninterrupted data flow so that data scientists can analyze it seamlessly.

For the past couple of years, companies have been hiring data scientists relentlessly. As a result, now they don’t have enough resources to provide their data scientists with the required infrastructure, which automatically makes data engineering one of the most prominent digital skills to have in 2019.
Apart from being proficient in programming, data engineers also need to be proficient in Hadoop, MapReduce, Hive, MySQL, Cassandra, MongoDB, NoSQL, SQL, & Data streaming and programming.

3. Industry Drastically Lacks AIOps Engineers

Quick definition: AIOps for data science/machine learning solutions is what DevOps is for traditional software development.

The abundance of data scientists (only in comparison, the industry still needs a lot of data scientists) has not only increased the demand of data engineers, but it has also triggered the demand of engineers at the deployment end (AIOPs). The rough chart below sheds more light on it.

data science machine learning career trends 2019

If we consider the current state of AI in the corporate world, the industry has enough resources focused on training models. But every model needs regular data and model versioning at the deployment end to ensure that the model continues to meet a business’s dynamic demand. And there, the industry faces a drastic lack of resources currently. So, all in all, this area currently presents heaps of opportunities. And the technology stack you need to learn for that includes frameworks such as TensorFlow Serving, Docker, Kubernetes (K8s), and Kubeflow.

4. Python Is the Present & Future

On the internet, there are already tons of resources on Python Vs R Vs SAS. But when it comes to machine learning and data science, it is already established (although arguably) that Python is the way to go, because it has the packages specifically designed for these jobs.

For beginners the trouble is that lots of tutorials and courses on the internet are based on R. For instance, on e-learning platform Data Camp, roughly 2/3rd of data science and machine learning tutorials are based on R, only 1/3rd in Python. But if you look at their respective communities, the Python community exceeds the R community by a great margin.

Now, I am not recommending that you don’t learn R at all. It is useful for a number of purposes. But if you are aiming to build a career in machine learning & data science, you should rather spend more time on mastering Python. Besides, most of the deep learning frameworks you will use such as TensorFlow, PyTorch, and are all based in Python.

5. A Portfolio Is a Must

Now, being someone who is trying to enter the data science and machine learning world, this part can be a little tricky. These are new technologies, so, there is a slight chance that you have experience working on related projects. And employers are also aware of it. But that shouldn’t stop you from building a portfolio.

Online portals like Github and Kaggle offer you the platform to showcase your work on whatever individual projects you are pursuing – as a part of developing a new skill. Pretty much, every employer would ask you for Github and Kaggle profiles in the present scenario. So, be ready with them, instead of excuses.

Concluding Remarks

The rapid growth of the digital landscape will continue to require professionals to constantly update their digital skills. For tech-savvy professionals, it means loads of new opportunities, and new horizons of possibilities what they can do with the technology. But in order to take advantage of this dynamism, professionals need to stay abreast with the on-going state of the digital landscape all the times.


Digital Skills

Around the world, across the industries, C-suite executives are concerned about the widening digital talent gap in their organization.

AI, big data, cryptocurrency, cyber-security – with so many technologies creating buzz at once, it is becoming increasingly difficult for organizations to determine which skill set they need to invest in.

Here are top 10 essential digital skills that you must have on-board to succeed in 2019, whether you are an organization aiming at transformation or a service provider delivering next-gen services to clients.

Data Analysis

digtial skills 2019 data analysis data science data analytics

With today’s advanced analytics tools, companies now have the means to analyze heaps of untapped data they have about their customers and organization. But they also need expert data analysts and scientists who can efficiently use these analytics tools to do all sort of analysis work (descriptive, diagnostic, predictive, and prescriptive) on that data, interpret it, and come up with crucial insights.

Besides analysis, the data science team should be especially skilled in the visualization part in order to showcase data and create reports that are easily understandable for the management and can assist them in making decisions.

Data Engineering

digital skills 2019 data engineering

Data engineering involves building tools and infrastructure that data analysts/scientists use. While data science focuses on analytics, data engineering is more about data consolidation and warehousing. It is essentially software engineering whose primary purpose is to keep data clean and flowing and deploy data insights at scale.

On the tech side, SQL, Java, Python, Hadoop, and Linux are the hottest data engineering skills currently. In fact, according to a recent study by Stitch Data, the demand for data engineers exceeds the demand of data scientists.

Mobile Expertise

digital skills 2019 mobile development expertise

No business needs a reminder that it needs to adopt a mobile-first approach in current dynamics – be it customer apps, content, or internal communication. The mobile computational environment in itself is evolving constantly. So, it is important that developers and marketers stay abreast with the latest mobile trends and be proactive in delivering customers an optimized and state-of-the-art mobile experience.

And in 2019, mobile expertise must not be limited to smartphones or tablets – there is a whole new generation of mobile devices hitting mainstream adoption such as wearables, IoTs, and more.

UX Design

digital skills 2019 UX design

UX design may sound nothing new, but with user’s attention span constantly declining across platforms, focusing on it has become all the more important. In current dynamics, UX isn’t just about visually appealing UI and tried-and-tested navigation. It has become more of a creative-meets-analytical type of role, where every decision is backed by data rather than just guts.

Today’s UX designers also need to think in terms of multi-platform since modern customers’ buying journey span over multiple platforms. So, it is important to deliver a consistent digital customer experience across multiple platforms to ensure a smooth purchase experience.

Machine Learning

digital skills 2019 machine learning

Machine learning is unquestionably one of the hottest digital skills in demand today. From voice assistants to data analysis and self-driving cars, there are tons of use cases of this futuristic tech across industries. In fact, all the other digital skills listed here has or may have some use of machine learning for better efficiency.

However, the AI/machine learning ecosystem is quite vast and is mostly exclusive to research currently. Only the supervised learning part of it has corporate applications as of now. So, it is crucial to know the current state of machine learning in the corporate world, how your business can leverage it, only then invest in acquiring the required skilled resources.


digital skills 2019 blockchain cryptocurrency

Thanks to the Bitcoin buzz, the tech world is now aware of blockchain (even if many still don’t understand it). Blockchain (or distributed ledger) has given rise to decentralized applications, which are inherently more secure and transparent. Apart from its widespread use cases in the finance sector (cryptocurrency), today, the tech community has found a number of other use cases for blockchain such as crowdfunding, file storage, identity management, digital voting, and more.

Building blockchain-based applications requires skills such as networking engineering, cryptography computing, database designing and programming languages (C++, Java, Python, Solidify, etc.).

Related: How AI is driving the next phase of growth in Fintech


digital skills 2019 augmented virtual reality AR VR

AR/VR is already transforming the gaming and entertainment industries and is also gaining wide adoption in media, marketing, advertising, health care, and manufacturing. Businesses of retail, travel, and many other industries have already begun to provide AR capabilities in their apps.

Besides these, AR/VR has opened a whole new world of possibilities how people will consume content in the near future. Currently, video is the most popular mode of content consumption. But as AR/VR based interactive content become easier to create and easier to access, it will naturally surpass video.


digital skills 2019 cybersecurity network security

Data breaches are the biggest threats of the digital age. And when they happen, they often result in long term financial loses for a company. And as the security measures develop and evolve, so do the threats. So, network security or cybersecurity is undoubtedly one of the most important digital skills to have on-board in today’s business environment.

In fact, according to a recent ESG report, cybersecurity has topped the list of the problematic shortage of skills in organizations globally. And over the past few years, the concern has only grown (from 42% in 2015-16 to 53% in 2018-19).

Cloud Computing

digital skills 2019 cloud computing edge computing multi-cloud

Cloud adoption continues to grow. According to LogicMonitor’s Cloud Vision 2020 survey, 83% of enterprise workload will be in the cloud by 2020. To accommodate cloud adoption, migration, and upgrade, organizations need network engineers, cloud architects, developers, and system administrators with relevant cloud computing skills.

However, today the cloud is not the same decade old cloud. From multi-cloud to edge computing, it has evolved a lot and organizations need to keep the latest trend in check and regularly upgrade their cloud strategy to make the most out of it.

Social Selling

digital skills 2019 social selling

Social media has matured over the past decade. It is no longer exclusive to connecting friends and communities. Serious business happens on it every day. Engagement on social media is far better than traditional mediums. For instance, LinkedIn’s InMail open rates are 300% higher than email. And given the nature of the platform, the business world has moved away from hard selling to value-based selling, where mutual trust and relationship with clients/customers is of the highest priority.

So, in current dynamics, having a marketing team with expert social selling skills is must for continuous growth of the organization.

Concluding Remarks

The skill gap is the most prominent threat that looms over the business world today. And multiple reports warn that it will get worse in the near future. It is imperative for C-suite executives to react to this threat and come up with ways to handle the widening digital talent gap in their organization.

And in case we missed mentioning any digital skills that you think are crucial in the current digital age, let us know in the comment section below.


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