Data science is a constantly evolving field that touches various industries including business, healthcare, finance, and education.
Resultantly, there’s been a significant shift in the type of hiring organizations are doing, which is much in favor of data science.
To fuel the demand for data scientists, companies have stepped up hiring in niche areas.
Experts in mathematics, programming, statistics, data analysis, or machine learning are highly in demand right now.
Given the status quo, start updating your skills on a regular basis.
Also, what matters most is the number of skills you can actually pick up in very little time.
Since you are home due to the pandemic situation, utilize time by following the steps below and push your career in data science further.
Don’t shy away from coding
As a data scientist, you must be comfortable with coding and with handling a variety of programming tasks.
Your programming skills should ideally combine both computational and statistical abilities.
Additionally, you should be able to handle large volumes of real-time data and apply statistical models to deduce results.
Some preferred programming languages among data scientists today are Python, R, Scala, Clojure, Java, and Octave.
So master a few or one of them for guaranteed success.
Once you are comfortable and feel confident about your programming skills, start solving real-world problems and case-style puzzles frequently.
This will make you better equipped for business data challenges.
Equip yourself with conceptual and technical knowledge
If you are an IT professional or an analytics manager or a banking and finance professional or for that matter, even a marketing management intern, now’s the time to upskill yourself.
Professionally designed courses in data science can actually put your career on the right track.
Also, you can master skills and tools like statistics, hypothesis testing, clustering, decision trees, linear and logistic regression.
Additionally, you can develop expertise in R Studio, data visualization, regression models, Hadoop, Spark, PROC SQL, SAS macros, statistical procedures, tools and analytics.
If you enroll into an online course, the best thing is you get to do all this and much more in an instructor-led virtual classroom environment, from the comfort of your home.
Start by enrolling for an advanced certification program in Data Science.
You can also checkout other Naukri Learning courses to upskill yourself as a professional.
Tap into unused sources of data
Your company or business is already sitting on a huge archive of data that is growing by the minute.
This database is mostly raw or unprocessed, and needs in-depth analysis.
With the power of data analytics, you can uncover new truths in your business’s methodology.
Data science can help you come up with novel solutions; for instance a fresh sales technique or project management approach.
Due to daily mundane tasks, you may lose sight of the underlying innovation that can revolutionize your business.
A big breakthrough can come with the power of Data Analytics.
Update your working style by spotting trends, extracting insights and making business predictions.
Additionally, with advanced analytics and acquired machine learning skills, you can tap into this rich vein of experience and generate predictive models for your organization.
Since machine learning has the ability to create accurate models to guide future actions, start applying it to drive revenues or profits or even customer loyalty.
Lastly, focus on the questions you want to answer for your company
Correlations and patterns from disparate, linked data sources yield the greatest insights and transformative opportunities.
Data Science has the potential of solving complex business problems.
It also opens new doors for fresh business opportunities.
In order to make the most of your data science skills, focus on questions you really want to answer for your employer or business.
This is a shift that has the potential to transform your perspective altogether.
Thereby, it will make you adept at coming up with smarter business solutions.
Thus, as a data scientist, you must learn to decipher the most relevant data from irrelevant noise.
Also, try to avoid creating a silo effect or focusing on narrow views.
All the best!