Top 5 mistakes data scientists make that can cause their careers to stall
IT is a dynamic sector of our economy. That means that it is critical that you are a dynamic employee and participant. At its core, being complacent and resistant to change can decrease your career prospects and promotions.
Being in the industry for over 30 years, I have spoken with many lead, mid level and entry level Data Scientists. Based on what I have heard over the years from these Data experts across all industries and company sizes, here are top 5 mistakes Data Scientist make in their career.
1. Poor communication skills
One of the most common missteps of any network / system professional can make in their career is a lack of communication with your boss and other stakeholders.
In today’s business world, IT touches everyone.
That is why it is essential to always keep leaders and other company stakeholders informed of potential outages, bottlenecks, and suggestions on how to improve the overall performance of the network. This shows your employer that you care about how your work impacts the overall goals of your company which in turn demonstrates your ability to handle more complex responsibilities and high level responsibilities.
VP’s I work with have shared, failing to communicate timely with your boss can often lead to missed opportunities mostly because you are not thought of as someone that they can count on.
Another important aspect of your communication skills is how you communicate with your boss and other employees especially those that fall outside of the IT realm (e.g. finance, marketing, sales, etc). When working with other individuals, it is important that you appreciate that you represent the entire IT department. For some, the nature of IT work is complex to understand, so the simpler you can make it for someone, the better. It can be easy to get frustrated and have a short fuse when someone does not pick up quickly on what you are saying. But, it is crucial that you maintain a level-head and try your best to reword it in a way that makes sense to users. If your boss is able to see you as someone that communicates effectively, efficiently, and passionately you will set yourself miles ahead of your IT peers.
My experience over the years in helping hiring managers fill Network / System administration roles, those with strong communication skills are hard to find and are elevated in their career quicker than most.
2. Not honing in on a specific industry
Unlike other IT professions, it is essential in data science to specialize in a particular domain. The quantitative methods and technologies are well known by most candidates for data scientist roles. However, having specific and in-depth knowledge of a particular domain allows one’s analysis to be carried out in a more targeted and useful approach. A CIO I talked to recently said this is critical, because data scientists are in a unique position to offer insight into predictive outcomes and the potential consequences of said outcomes. These data scientists know about the less quantifiable factors that influence a particular domain and business.
3. Job hopping
Resistance to any technological advancement is a detrimental habit in any career especially in IT. But, key technological innovations that have already started to make significant impacts in IT infrastructure are:
- Automated Scripting.
According to McKinsey 2017 IT-as-a-Service Survey, 82 percent of respondents stated that they had implemented DevOps practices in some part of their organizations.
In order to stay competitive in the IT marketplace (especially one rocked by a pandemic and a looming recession), network engineers and system administrators should make the effort to learn about DevOps and how the mindset can add great value to a company.
Learning new automated scripting/programming languages may not be an essential skill right now. However, in the near future, you will start to see this skill as a requirement on job postings. Or perhaps your current job will change to require some basic automated scripting/programming knowledge.
The future of network / system engineering lies partly in Software Define Networking (SDN), and in order to keep up with SDN you must have basic skills in programming languages and automated scripting.
4. Failing to develop a career road map
One way to help you in making thoughtful career decisions and in avoiding job hopping is developing a career road map. A career road map is a tool that you can use to develop a framework of how you want your career to go. A great exercise to conduct is to think about where you want to be short term (3-5 years) and long term (10-20 years) from now in your career. What is your end goal? I have found your educational sponsor/advisor is a great resource to help you through this process.
Once you have that nailed down, come up with a couple different paths based on what kind of skills you need, what kind of promotions you want to get, and what kind of domain you want to work in. All of these factors go into shaping your career.
An important note is that you need to remain flexible while traversing your roadmap. It should act as a system that can allow you to measure your progress and identify the right opportunities, but not as a rigid structure that must be followed to a T. Do not let the map hold you back. Think of it as a map of the US. There are many routes you can take to get from the east coast to the west coast, but as long as you have a sense of where you’re going you can make it to your destination.
5. Not learning outside of work
As we all know, the only thing that is constant is change. The IT industry is constantly evolving. In order to keep pace and advance your career you need to always be learning and developing new skills while you are not on the clock. A good habit is to pick one new skill you’re going to train yourself on and come up with a schedule. Some examples of skills to learn such as Python, machine learning, and Apache Spark are discussed in our article: top ways for Data Scientist to stay competitive in today’s market.
Hiring managers look for employees that can demonstrate the ability to learn new skills on their own long after their formal training has ended.
By not over relying on your employer to teach you new technologies, it can allow you to teach yourself things you’re personally interested in and keep your job fresh. This also will allow you to introduce new technologies that can help the business and your career.
Taking time each year to learn about new tools or platforms will keep you actively engaged in your own career while also setting yourself apart from others in your company. Some new technology that CIO’s look for their Data Scientist to have include:
When it comes down to it, slight adjustments can have positive results on career trajectory and prospects. Avoid these mistakes by investing into yourself by reading books, getting a mentor, and being mindful of your work.