Data science is one of the most sought-after fields with the higher need to make sense of large and complex datasets in organizations. According to the Emerging Jobs Report of LinkedIn, the data science market can reach a value of $230.80 billion by 2026. This exponential growth will create around 11.5 million data science jobs by 2026, as reported by the US Bureau of Labour Statistics. Interested IT professionals can consider data science for making a long-lasting and rewarding career.  

What is Data Science and Why is it Popular?

Data science is a field that uses scientific procedures, methodologies, algorithms, and systems to get meaningful knowledge and insights from structured and unstructured data. It is an integration of various disciplines that eventually helps with effective data-driven decision-making, problem-solving, and driving innovation. For example, data cleaning, data visualization, statistics, data analysis, etc.   

What do Data Scientists do?

A data scientist is a professional who practices data science to analyze complex data and get actionable insights for real-world use. They are responsible for performing various tasks in an organization such as –

• Gather, prepare, clean, explore, and validate data for businesses to make the right decisions and solve business challenges.
• Develop machine learning (ML) models and deploy them for real-world applications.
• Identify hidden trends and patterns using algorithms and modules.
• Monitor models and convey findings to non-technical stakeholders.
• Develop efficient data strategies with the support of other team members and leaders to achieve organizational goals.

Solid Reasons to Become a Data Scientist

1. Growing demand: Companies across the globe are looking for skilled data science professionals to extract insights from the ocean of their data. This makes data science as one of the most in-demand fields with no signs of reduction. A 23% rise in data scientist jobs is projected between 2020 and 2030 (Source: US Bureau of Labor Statistics).
2. Lucrative salaries: The average worldwide salary for a data scientist is $105,000 annually, according to Glassdoor. However, it may vary based on skillset, location, company size & type, and experience.
3. Great impact on an organization and planet: By getting into a data science career, you can make a significant impact as a leader in this field both in your organization and the world. You can automate repetitive and routine tasks, saving your organization’s time and money.

Automation will allow your company to ensure the efficient optimization of resources. Data scientists can also help save lives by developing precise climate models and weather forecasting technology to fight against the negative effects of climate change.

4. Excellent career growth opportunities: With a strong background in data science and learning passion, you can work up to accelerate your career as a senior data scientist, lead data scientist, data engineer, ML engineer, and more profiles. Since data scientists often interact with C-suite executives and other senior members of a company, they can go on to executive roles such as chief data officer.

Data Scientist Qualifications and Work Experience

• At least a bachelor’s degree in statistics, computer science (technology), engineering, or mathematics.
• A master’s degree in ML, AI, data science, or related discipline.
• A basic knowledge of quantitative subjects.
• Essential skills related to the data science field.
• Practical experience in real-world projects
• Contribution to open-source projects or data-related projects
• Constant learning through online data science certification and courses, workshops, etc. to stay tuned with the new trends and technologies.

Top Skills to Emerge as a Talented Data Scientist

A data scientist is a highly qualified, well-trained, and certified professional with a range of technical and soft skills.

Technical skills

• Programming

A good knowledge of programming languages such as C/C++, JAVA, Python, and R is significant for tasks where performance is essential.

• Data visualization

The ability to represent data findings in visually appealing and comprehensible formats.

• Machine learning

Learning and applying ML algorithms and concepts to identify hidden patterns and predict outcomes.

• Deep learning

Understanding deep learning frameworks is important to develop and train neural networks for structured data.

• Mathematics, probability, and statistics

Math skills and probability are required to understand ML algorithms. Since statistics is a part of data analysis, understanding this discipline is highly important.

• Database management

Developing expertise in important databases for efficient data storage and management.  

Soft skills

Good communication skills are essential to convert complex findings into actionable and concise insights for non-technical and technical stakeholders. Other crucial soft skills include a natural curiosity to discover data for hidden patterns and ask questions, critical thinking to approach problems strategically, business intelligence to support the decision-making process, and strong data intuition.  

Step-By-Step Guide to Becoming a Data Science Professional

1. Earn a bachelor’s or an associated degree in a related field like STEM.
2. Develop proficiency in primary programming languages such as Python, R, etc. based on the job you are applying for.
3. Learn core skills such as machine learning, big data, data manipulation, statistics, and more (as mentioned above).
4. Attend conferences, networking events, and meetups in the data science field.
5. Join the best data science course to earn an in-demand certification and validate your expertise.
6. Seek internships or apply for entry-level jobs for practical experience. For example, data analysts, data scientists, and data engineers.
7. Participate in online data science forums, communities, and social media groups.

Conclusion

Data science is a securely growing and in-demand field with Harvard Business Review describing it as ‘the sexiest job of the 21^st century’. Data science certification programs ease the journey to make a rewarding career in the data science field. Hopefully, this data science roadmap provides a structured and step-by-step guide to becoming a data science expert and accelerating your career in data science.