Data Scientist: Stop searching for that data scientist unicorn

Posted on Oct 29, 2019

Instead, focus on hiring the technical skills needed to build the team, and the soft skills needed to work on the team

The data science unicorn is a somewhat mythical person who is a leader in data science, technology, and business. Of course, these candidates practically don’t exist, nor do they necessarily make strong team members. As data science teams have grown, businesses have moved away from trying to find that one person to fill different roles; instead, companies have realized the benefits of hiring employees with specialized, complementary skills.

Data scientists are still in high demand. In fact, data science job postings have increased by 256% since December 2013. It seems that no industry is immune to this data scientist shortage, as global companies continually seek qualified talent. And luckily, this search has become more niche. While many job postings still say “data scientist,” the descriptions are beginning to lean towards more specialized needs. Furthermore, companies are seeking candidates with strong soft skills that can complement a data science team.

Bob Rogers, the chief data scientist at Intel’s Big Data Solutions, recognized this change back in 2015. Rogers noted:

“It’s true that having advanced knowledge of mathematics and programming is fantastic background for a data scientist,” he says. “But, in any company, you won’t find just one data scientist doing it all—just like Michael Jordan couldn’t have scored so many points without Scotty Pippen at his side, data scientists all bring their own skills to the table that together build an ideal team.”

The new data science team

The specialties within data science are numerous and growing. From data mining and statistical analysis to deep learning and cloud computing, data scientists have options when it comes to choosing where to focus. And companies have options when scaling a data science team.

When building a team, it’s critical to understand how the project will be introduced, maintained, and scaled not only in terms of technology but also in terms of individual roles within the project. Some companies opt to build a team using an IT-centric structure. Those that use this option typically utilize some sort of machine-learning-as-a-service (MLaaS) software that has low barriers to entry. The entirety of the project, including data preparation, model training, interface creation, and deployment all happen within the IT infrastructure led by the IT team.


Another option is using an integrated structure. Here, the data science team prepares the data and trains the models, and the IT team then takes over to evaluate and deploy the models. This approach requires a robust data science team with complementary skill sets. A third option is to run the entire process, from data preparation to deployment, within a dedicated data science team. In this scenario, the data science team must have IT infrastructure knowledge and skills to get the models to deployment.

Often, companies build a team that incorporates data scientists, IT employees, and business analysts, or people that can translate findings to business value. Open communication between these three teams working as one reduces the risk of models not being deployed or improper infrastructure issues. Of course, building the data science part of the team can be difficult with the current skills gap. And with that scramble to find talent, new roles and specialties are emerging in the data science world.

In-demand data science specialties

While it has always been difficult to fill roles such as Chief Data Officer or even an experienced deep learning engineer, there are new positions that have risen in the last few years that companies want to fill.

More companies are applying data-driven methods to cybersecurity in order to improve the prevention of breaches. Whereas security approaches tend to be applied post-breach, data science has been helping companies tackle cybersecurity both pre- and post-breach. Using supervised machine learning, this technology can find behavioral features from executables run in isolated environments, which makes it harder for malware authors to go unnoticed. Anomaly detection post-breach means that attackers who already are inside the system can be found using self-learning models that understand normal behavior. With the surge of cybersecurity hacks and their rising costs to enterprises, it’s no wonder that companies are recruiting data scientists that specialize in security.

Another in-demand position in the data science world is the financial data scientist. Finance professionals have long been performing data science tasks such as risk assessment and forecasting. Data science helps improve and automate many of these tasks. A candidate that understands finance and also has a robust knowledge of data analysis, programming, and statistical techniques becomes a financial data scientist that can dramatically improve company performance.

Don’t try to find the unicorn

Companies ramping up a data science team shouldn’t waste time trying to find the unicorn, because it will slow down hiring drastically. Instead, they should focus on the technical skills necessary to build the team and the soft skills needed to work on the team. In my opinion, large enterprises will likely continue to look for security and finance specialists, as more candidates are likely to get training in these areas to fill this need.

While artificial intelligence and machine learning can revolutionize a business, these technologies cannot do much without proper model building and infrastructure in place, making it worthwhile to slow down in order to scale correctly.

About Author

Vivian Zhang

Vivian Zhang is the CTO and School Director of the NYC Data Science Academy. She started the NYC Open Data meetup group. She earned her M.S. in Computer Science and Statistics and B.S. in Computer Science. She is...
View all posts by Vivian Zhang >

Related Articles

Leave a Comment

Google October 31, 2021
Google Check below, are some absolutely unrelated web sites to ours, on the other hand, they're most trustworthy sources that we use.
Google September 9, 2021
Google Here is a good Weblog You may Find Fascinating that we encourage you to visit.
CBD For Dogs December 10, 2020
CBD For Dogs [...]just beneath, are quite a few totally not connected internet sites to ours, even so, they're surely really worth going over[...]
RDP with Windows 10 September 3, 2020
RDP with Windows 10 [...]Every after inside a even though we opt for blogs that we read. Listed beneath are the most recent sites that we select [...]
Write My Essay July 24, 2020
Write My Essay [...]Wonderful story, reckoned we could combine a number of unrelated information, nevertheless genuinely worth taking a appear, whoa did 1 discover about Mid East has got far more problerms at the same time [...]
DataAnalyticsCourse DataAnalyticsCourse May 26, 2020
I am impressed by the information that you have on this blog. It shows how well you understand this subject. data analytics course data science course big data course big data course 360DigiTMG
Data Science Training in Hyderabad April 11, 2020
Inspirational, I am feeling motivated and now work harder to start the career in Data Science, hope will get similar success. Thanks for sharing your Data Science experience.Data Science Training in Hyderabad
laxmi pratyusha November 29, 2019
The information you provided is very useful and it is very interesting.
URL November 28, 2019
... [Trackback] [...] Read More: [...]

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI