Data science isn't just about acquiring skills; it's also about comprehending the business context in which data science is applied, says Sonya Hooja, COO and co-founder of Imarticus Learning.
In the ever-evolving realm of tech, change is the only constant.
And this holds particularly true in the field of data science.
With technology advancing at breakneck speed, individuals must keep pace with cutting-edge developments to remain relevant in the industry.
Nearly 60 per cent of hiring managers say that data science and analytics roles are the most difficult to fill. The challenge arises from the shortage of individuals possessing the right skill set in the current workforce.
This underscores the fact that upskilling in the realm of data science is not merely a desirable option but an absolute necessity to maintain a competitive edge in the industry.
- You can post your workplace and career-related questions HERE.
Considering the abundance of available resources, I would like to share nine tips to acquire the right skills required to succeed in this field.
1. Foundation Matters
Before diving headfirst into data science, start by learning basic computing skills including Excel, SQL and statistics.
2. Soft Skills
Data science isn't just about acquiring skills; it's also about comprehending the business context in which data science is applied.
Effectively communicating insights and recommendations to non-technical stakeholders is crucial.
3. Hackathons
Embrace a perpetual sense of curiosity and competition. Participate in hackathons to stay relevant in this ever-evolving field.
4. Build A Portfolio
Take an extra step and build a comprehensive portfolio that showcases your problem-solving approach. This can significantly enhance your chances of securing your first job.
5. Data Handling
Get comfortable with handling large volumes of data through programming languages.
Familiarise yourself with at least one data visualisation tool such as Tableau or Power BI.
6. Hands-On Learning
To truly gauge your readiness, you must get hands-on experience. So extract insights from datasets available on platforms like Github, Kaggle and Data.gov.
You can determine if a ship can float or sink by placing it in water.
7. Community Involvement
Join data science communities and forums like Kaggle, GitHub or Stack Overflow.
These platforms are where data scientists worldwide exchange knowledge and learn from each other.
8. Build A Strong Online Presence
Share your knowledge and insights through blog posts, LinkedIn, and other professional platforms to boost your personal branding.
9. Stay Informed
Keep up with the latest research papers and advancements in data science.
The field is constantly evolving and there's a wealth of knowledge in research papers.
Navigating the ever-changing landscape of data science may seem daunting but, with a systematic approach to upskilling, you'll not only weather the storm but also ride the waves of change.
Upskilling in data science isn't merely about staying current; it's about being adaptable, resilient and always ready to learn.
It's about setting the pace and keeping up with it.
- You can post your workplace and career-related questions HERE.
Sonya Hooja is COO and co-founder of Imarticus Learning, an ed-tech firm that offers training in financial services and analytics.
