How to be a Data Scientist in 2024?

Table of Contents:

• What is Data Science?
• Is Data Science a good career in 2024?
• What Skills should a Data Scientist have?
• How can I become a Data Scientist?
• Conclusion 
• Bonus Points

What is Data Science?

Data Science is an analytical domain that has skyrocketed to popularity in recent years.  In layman’s terms, Data Science involves analysing data to extract meaningful insights. Professionals working in this field, called Data Scientists, utilise a combination of Computer Science, Mathematics, Statistics, and even Engineering to find hidden patterns in data sets, which can generate helpful conclusions.

Is Data Science a good career in 2024?

Data Science is not just a good career option – it is one of the most highly sought-after roles in today’s  job-market. 

• High Demand: The US Bureau of Labor Statistics reported that Data Science careers are projected to grow by over 30% between 2023 and 2025, at much faster than other roles.  As more organisations adopt data insights, this demand is only positioned to grow further. 
• Sizeable Compensations: According to BLS, the median pay for a Data Scientist in 2023 is around $50 per hour, or $108,020 per annum. That figure is expected to rise, as the demand for Data Scientists is also set to rise over the next few years. 
• Opportunities Across Industries: Data Scientists can work in virtually any industry that utilises data to guide decision making. This can include Healthcare, Construction, Education, Public Administration, Engineering and of course, IT. 
• Connect IT to Business: Data Scientists have been referred to as the ‘bridge between Business and IT’ (datasciencedojo.com). This means that Data Scientists are able to bring perspectives from data that can revive business efforts and enhance profitability. 

What Skills should a Data Scientist have?

Here are the skills required for Data Scientists, from beginners to seasoned Experts:

• Technical Proficiency: 

  • An advanced understanding of Mathematics, Statistical Analysis and Calculus are a must, as Data Science is built upon  the principles of these domains. 
  • Software Engineering and Programming skills are also essential for this role, particularly proficiency in NoSQL, SQL, R and Python. 
  • Data Scientists are also highly educated in Machine Learning, Cloud Computing, Data Visualization, Artificial Intelligence, Big Data and Data Manipulation. 

• Soft Skills: 

  • This role  demands strong soft skills. A Data Scientist must be a strong communicator capable of conveying complex conclusions to a non-technical audience. 
  • Analytical and critical thinking skills are also key to approaching tricky problems and bringing effective solutions. 
  • Curiosity is also a useful skill, as it helps Data Scientists probe a problem beyond surface level and be self-motivated to investigate multiple approaches. 

• Business Acumen:

  • While Data Science may not seem like a typical business role, such as Operations, Sales or Human Resources, that could not be further from the truth. 
  • For most organisations today, Data Science is orchestrating their strategies, from product design and branding to sales pitches and digital marketing campaigns. 
  • It is important for Data Scientists to understand how their insights can inform, shape and even redirect business decisions, and the consequent implications. 

How can I become a Data Scientist?

• Start with Education: 

While some Professionals enter the Data Science industry in other ways, it is usually best to start with a relevant Academic Degree. Consider your budget, learning requirements, university, faculty, curriculum and accreditation before choosing your Program. 

If you are on a budget, working full-time and prefer distance learning, UniAthena’s Master in Data Science is a good option. If you have leadership aspirations in the Data Science world, why not check out our MBA - Business Intelligence and Data Analytics? 

If you are still exploring the domain, UniAthena’s Basics of Data Science is for you. Free-to-Learn, 100% Online and Self-Paced, the course offers beginner-level insights into the domain. Whichever option you choose, educating yourself is the first step towards a Data Science career. 

• Amp Up Your Data Science Certifications: 

After completing your degree program, you can keep updating your portfolio with relevant certifications. Chances are, as a fresh graduate on the hunt for a job, you will be limited in your time and budget. This is where UniAthena’s  Data Science Courses come in handy. 

You can refresh and revise your Machine Learning knowledge, and add an impressive certification to your portfolio, with UniAthena’s Diploma in Fundamentals of Machine Learning and Executive Diploma in Machine Learning. These courses allow you to keep your Machine Learning skills up-to-date, and depicts your commitment to learning and growth. 

This is also the perfect opportunity to cultivate a business mindset. UniAthena’s got you covered here too! Our MBA Essentials with Data Visualization offers key insights into management domains while refreshing your data skills. 

• Build Skills and Connections:

While hunting for jobs, you can take up personal projects to enhance your portfolio and keep your skills polished. Showing that you dedicated this period towards professional development is something any Hiring Manager would be impressed with. 

If you prefer to work in a community, try joining Kaggle. This Data Science platform hosts competitions that will challenge your capabilities, put your expertise in the spotlight and connect you with like-minded Professionals in the industry. Kaggle will also be a great place to learn new Data Science techniques and use public data sets for your own projects. 

• Be on the Lookout for Job Opportunities

While it is true that the demand for Data Scientists is at an all-time high, keep in mind that the field is also experiencing a constant influx of fresh talent. Competition will inevitably rise, and the best way to stay ahead is to hunt for opportunities yourself. 

Be active on job-seeking platforms like LinkedIn, brush up your Resume, and attend industry events like conferences, workshops and webinars to build your knowledge and professional network.

Conclusion 

Data Science is a lucrative field, but aspirants must still build key skills and fulfill data scientist requirements to stay ahead. The blog details the key skills required for data scientists in 2024, along with recommendations for flexible and affordable data scientist certification courses. 

A Data Scientist roadmap was also offered, exploring the different steps aspirants need to undertake for success. Building the skills, credentials and community connections is the first step to living your dream data science career. 

Bonus Points:

• Data Scientists and Data Analysts do not perform the same function. While Data Analysts use structured data to address existing problems, Data Scientists work with more advanced data sets. They also develop their own programs, algorithms and tools. 
• The best way to stand out in the crowd of Data Scientists is to build your business acumen. Companies prefer well-rounded candidates, and business skills will ensure that you are involved in the application of data insights for commercial objectives.