A career in data science is full of opportunities. With an average annual compensation of $210,000, a job in data science is the third highest paying in the world. So, pursuing a course in this field is the right step forward for working professionals seeking a switch to a more rewarding career.
However, even after completing a comprehensive data science course, a lot of aspirants are not fully aware as to what a data science job entails. In this competitive job market, finding a job in the data science domain can be a challenge even for professionals from IT background.
If you have successfully completed the data science course, chances are you have already worked on some workable mini projects to put your knowledge to test.
However, there are more ways to stay up to date with the industry trends and continuously assess your understanding as the competition gets tougher.
Your Next Move After Data Science Course
You have gained your foundational knowledge after completing the data science course. Next up, you can sharpen your skills to effectively tackle big enterprise challenges.
As a vast and dynamic domain, data science finds its place in a lot of disciplines. So, what solution-building activities can working professionals look into to probably get their first data science job:
- Clean and categorize data
- Standardize data and manage storage
- Establish data pipelines and absorption methods
- Manage data warehousing and organization
- Implement cloud and caching techniques for enhanced database interaction
- Utilize pattern recognition and algorithms to address intricate business challenges
- Train models and enable ongoing learning
- Visualize data and conduct impact analyses
One needs to have a comprehensive understanding of these activities to build an integrated solution.
Completing a Data Science course is an achievement for sure, however, the learning doesn’t stop just there. You have to keep on testing your knowledge to ensure it remains sharp and relevant.
Interview Kickstart offers many mock interviews in association with experienced interviewers with hiring backgrounds at FAANG+ companies.
Have a look at the video below to check how you can prepare once completing the Data Science course with Interview Kickstart.
Mock interviews can leverage to devise solutions, and demonstrate problem-solving capabilities to future employers.
Engaging in activities like these can serve as stepping stones in your journey towards attaining your dream break as a data scientist.
Work Towards Branding Yourself
In the fiercely competitive professional world we live in, it is essential to stand head and shoulders above the rest to get recognized. Here are a few activities you can work upon to project yourself as a brand once you finish your data science course.
â€Work as an Independent Contractor
Many enterprises offer freelance positions to professionals to work on live projects. This gives them domain-specific practical exposure and yields cost benefits to organizations. As a working professional, you can use your network to work on a few data science projects as an independent contractor.
Network Yourself:
Participate in online forums and boot camps. Attend live meetings and conferences. Meet people from data science to build your network and to stay updated with the latest trends in the data science domain.
Continue to Learn
Data science is an ever-evolving field that upgrades its techniques in a matter of weeks. You need to level up through regular learning to keep up the pace with these upgrades.
â€Build Your Resume
Build a powerful resume showcasing your achievements, including training sessions, conferences and meetups attended, and skills acquired.
â€Get an internship
Internships serve as great stepping stones for aspiring data scientists with limited project experience. Fortunately, a lot of companies offer internships so you can opt for one to start your career.
â€Skills Needed to Kickstart a Data Science Career
To start a rewarding career after completing a comprehensive data science course, one must possess proficiency in the following technical and leadership roles.â€
Technical Skills
- Proficiency in databases like Oracle or SQL
- Sound understanding of differential and integration calculus, linear algebra, and probability
- Good working knowledge of Python, R and SAS programming languages
- Efficient data wrangling skills
- Machine learning like regression analysis, reinforcement learning and classification
- Ability to work on complex data with tools like Spark, Splunk and Talend.
- Visualize results with various data visualization tools like PowerBI, Tableau, and Google Data Studio.
â€Leadership Skills
- Strong written and verbal communication abilities
- Effective problem-solving abilities
- Essential leadership skills
- Delegating abilities
- Ethical awareness
- Trustworthiness
- Motivation and positivity
- Adaptability
Pivot into the Data Science CareersÂ
Once you’ve gained decent practical experience of working on live data science projects as a consultant or intern, it’s time to pivot yourself into a data science career.
According to the data released by North Western University, one of the U.S.’s leading private research universities, nearly 37% of data science job postings cater to employees with 0-3 years of experience in data science.
Indeed, there are quite a few job roles in which data scientists are required. They can start at entry level and gain more prominent roles with experience, hard work, and perseverance.
Some of the work areas in which data scientists play a pivotal role are data analysis, machine learning, Tableau development, business analysis, data modeling, research science, data administration, and statistics, to name the most prominent ones.
Data Science Course Learning Conclusion
â€As data science is an ever-evolving field it’s poised to scale into more domains with every passing year. So, if you are launching a career in data science after completing a relevant course or are considering a career switch, expect to have a rewarding career ahead.
What to do after completing Data Science Course FAQs
What is the future of data science after five years?
Although some researchers foresee a large chunk of data science-related work getting automated within the next 10 years or so, there will always be requirements for professionals to understand business data and devise solutions around the same.
So, it’s fair to say that data scientists will remain a lucrative career option for the foreseeable future.
What is the highest position one can attain in a data science career?
After working in various data science roles for nearly 15-20 years and attaining career growth, the highest position one can attain is Director of Data Science.
In this position, the professional oversees all the data-related initiatives in an organization and plays a strategic role in driving decision-making at the highest level.
What educational background do data science aspirants need to have?
For data scientist aspirants, at least a bachelor’s degree in computers (B.Sc. BCA, B.Tech, etc.), information technology, mathematics, or statistics, is preferred.
However, with additional training and relevant experience, graduates from economics can transition into data science roles.
â€How can one stay updated with the latest trends and technologies in data science?
â€To succeed in the data science role, the biggest skill one needs to attain is to be a lifelong learner.
As data science is an ever-evolving field, one needs to stay updated every time by participating in online discussions, reading blogs and articles, attending workshops, seminars, and bootcamps, and networking with other professionals.
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