Are you wondering how to start your journey to how to start your journey to become a data scientist even if you have never done it before? Don’t worry, This article is designed to help you kickstart your journey toward becoming a successful Data Scientist, even without your experience in the field.
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Data Science with no Experience
Data Science is an in-demand career field with excellent job prospects and the potential for high growth. Organizations worldwide realize the power of the data they collect. Artificial Intelligence (AI) and Business Intelligence (BI) tools derive value from such data. They need Data Scientist professionals to use multiple data processing methods to prepare the data for AI and BI software consumption.
A Data Scientist analyses and interprets data and uses data analytics tools to enable organizations to improve decision-making. A strong background in statistics, mathematics, and computer science is expected. As per the Bureau of Labor and Statistics, Data Scientist jobs are expected to grow by 35% from 2022 to 2032, much faster than all other occupations.
Who is Data Scientist?
Let’s understand the basics before we get started. A Data Scientist collects and cleans large amounts of data. They use dashboards and databases for interpreting data to run experiments and solve problems. Data Scientists use a multitude of AI and BI tools to create these visual representations of data. A Data Scientist employs multiple technologies like machine learning, data visualisation, deep learning, relational databases, big data, exploratory data analysis, natural language processing, statistical software, and predictive modelling to create insights from data. Their work spans many industries, enabling businesses to optimise products and operations of the roles and responsibilities of a Data Scientist are:
- Collecting and identifying data sources
- Analysing massive amounts of structured and unstructured data
- Crafting strategies and solutions to business problems
- Working with multiple teams to develop a data strategy
- Discovering patterns and trends using various algorithms
- Mastering data visualisation techniques and tools
- Architect, implement, integrate, and monitor data pipelines
Data Scientist With No Experience – A Complete Roadmap
Mastering data wrangling, machine learning, big data, and data visualisation tools is mandatory for anyone wanting to become a Data Scientist with No Experience As per the New Vantage Partner report, 83.9% of organisations plan to increase their investment in data and analytics. This directly translates to increased demand for Data Science professionals. Let’s now focus on building a career in Data Science with zero industry experience. Here are steps to become Data Scientist :
- Step 1: Acquire Technical and Non-technical Skills
- Step 2: Earn Certifications
- Step 3: Build a Portfolio
- Step 4: Create Your Resume
- Step 5: Network With Experts
- Step 6: Look for Internships in Industry-specific Projects.
- Step 7: Seek Entry-level Data Entry Jobs
- Step 8: Build Your Brand
Step 1. Acquire Technical and Non-technical Skills
It goes without saying that you must first acquire and master technical and non-technical skills. You can go the traditional way and obtain a degree in Data Science or a relevant industry first. Pursuing the non-traditional path, obtain relevant certifications, such as a fast-track Data Science course, to mark the beginning of your career.
Technical Skills
Soft Skills
- Critical thinking to find solutions for problems from different perspectives
- Effective communication to deliver data-driven insights
- Proactive problem-solving to identify opportunities for solutions
- Ability to understand unique needs of business and leverage data to create results
Step 2. Earn Certifications
Employers value skills more than a college education, even if you have a degree in Data Science. Boost your profile with a few certifications in Data Science concepts. A Python or SQL certification will show employers that you are an expert. If you prefer to work with data visualisation, obtain Tableau or Power BI certification to get a strong start.
You can refer to this article – Top 7 Data Science Certifications That You Can Consider
Step 3. Build a Portfolio
Learning theoretical concepts is not sufficient to become a Data Scientist with No Experience. You need practical knowledge and experience. While you don’t necessarily need industry experience, you still need some work experience. This is where your portfolio will be of help. Work on Data Science projects on your own and build your portfolio.
When you sign up for Data Science courses with reputable organisations, the training course will include exposure to industry. This may be workshops, internships, or other projects where you can work on real data sets. You can also take up Data Science projects and post them on GitHub. This will show the hiring managers that you have practical experience with Data Science concepts.
You can refer to this article – How to Build an Impressive Data Science Portfolio?
Step 4. Create Your Resume
Build a resume that directs attention toward your portfolio. Personalise the resume for the job you are applying for. Understand the roles and responsibilities of the job and ensure that your resume highlights key skills needed for the job.
You can refer to this article – Data Scientist Resume – Guide and Sample
Step 5. Network With Experts
Communicating and interacting with accomplished Data Science professionals will place you in the right place at the right time. Look for local Data Science groups and become an active member. Participate in online forums, workshops, and networking events for Data Science professionals. Being aware of the trending topics in the industry will help you stay relevant. Many times, you can get great support from your peers if you are looking for Data Science jobs. It will also help you upskill and reskill based on industry demand. Remember, acquiring in-demand skills is crucial to staying relevant.
Step 6. Look for Internships in Industry-specific Projects
While you don’t need job experience to start working as a Data Scientist, you still need industry exposure. You can sign up for internships to work on projects specific to the industry you are passionate about. Data Science is used in every sector, and your proficiency in the industry will set you apart from the rest of the candidates.
Step 7. Seek Entry-level Data Entry Jobs
While the average salary for a Data Scientist is $123,455, the entry-level salary may be somewhat lower. You can earn a higher salary only after you gain industry experience. So, look for entry-level data entry jobs, even if they pay less. Unpaid internships are great ways to gain work experience to boost your portfolio. To build your resume, you can also look for Data Science projects in freelance job listings.
The entry-level jobs will open the door to success. Once you get your foot in, you can explore more opportunities by upskilling along the way. It is also possible to switch industries if you gain mastery of Data Science concepts. You can also consider part-time jobs to be your career.
You can refer to this article – How to Get a Data Science Full Time Job?
Step 8. Build Your Brand
The concepts of Data Science are straightforward. However, what makes professionals unique is their approach to problem-solving. Data Science jobs involve interpreting data, discovering patterns, and creating new meaning. Develop a business sense so that you can create actionable insights that will be useful for the C-suite leaders. If you are truly passionate about Data Science, find ways to create a brand around your persona, such as a blog, that will also help you advance in your career. Use social media wisely to connect with like-minded professionals and build your network.
Conclusion
The demand for Data Scientists will increase in the future, with every industry looking for data experts to make sense of the collected data. Futuristic businesses leverage data for critical decision-making as machine learning models can quickly identify patterns overlooked by humans. Data Science professionals are needed in a data-driven world to collect, store, organise, and analyse vast amounts of data to develop visual and impactful insights. Even though traditional degrees are still valuable, you can improve your skills with Data Science courses and stay competitive in this dynamic field even without any prior experience.
Data Scientist with No Experience: Guide for Beginners – FAQ’s
What is the educational background is required to start a career in data science?
No, it is not necessary to have a degree to becomw a data scientist, You just need to accquire relevant skills in statistics, programming (Python or R), machine learning, and data manipulation and visualization. Starting with foundational courses and gradually working on projects can help build the necessary expertise
How long does it take to become a data scientist from scratch?
Times takes to become a data scientist from scratch can vary widely depending on several factors that includes your prior education, experience, and the intensity of your studies and the resources available to you. However a rough estimation would be anywhere from 6 months to 2 years or more.
Do I need a formal degree in data science or a related field to become a data scientist?
No, you don’t need a formal degree to become a datscientist although Whila a degree in datascience, computer science , mathematics or a related field can be beneficial. Many recruiters value practical skills, and experience over formal education.
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