Many of us know that Data Scientists are highly educated professionals coupled with domain experience. They are usually master degree holders or Ph.Ds with strong communication and interpersonal skills. So, what are the essential skills for a person to become a data scientist? Can people from any stream aspire to become one? Are there any other careers in the niche of data science that less experienced or beginners can aspire to?
Why should you choose the Data Science field?
First off, if you are a candidate with an inherent passion to deal with data and to use this data to solve big business challenges, then data science is for you.
The Data Science niche is booming and there are immense opportunities in this field in almost every industry. From retail and e-commerce to healthcare and diagnostics to sports and entertainment, no field is untapped by data science.
Who can transition to be a Data Scientist?
Not everyone can become a data scientist right away. As already mentioned, domain knowledge is imperative to become a data scientist. As it is this knowledge that drives the Data Scientist in making important business decisions and while communicating them to the stakeholders.
Before we get to know what skills are required of a data scientist, let’s understand the various activities of a data scientist.
- Their job starts with determining the data-analytics problem that has the highest potential to bring change in the organization in terms of profits or business improvement.
- Identifying the right data sets required to solve this business problem
- Collecting the data that could be structured, semi-structured, and unstructured.
- Data cleansing, validating the data, ensure accuracy, and comprehensiveness
- Applying algorithms to analyze patterns and trends in data
- Interpreting the insights to make predictions
- Visualize data and generate reports
- Communicate the findings to the stakeholders.
Apart from domain knowledge, a typical data scientist is expected to bring the following skills to the table:
- Hold a degree or possess knowledge in mathematics, statistics, computer science, or management.
- Has impressive experience in these areas.
- Has the passion to take up challenges and solve them with the help of data
- Good written and verbal communication skills.
- Has substantial data visualizations skills.
How to become a successful Data Scientist?
With the help of self-analysis, if you could decide that Data Science is your place to be and Data Scientist is what you hope to become, then your ground-work starts here.
You might have all the essential skills to transition as a data scientist, however, you will need proper guidance, the knowledge of statistical languages and tools like Python, R, and Tableau, a good understanding of various Big Data tools like Hadoop, Spark, etc, and a road map.
Step 1 – Acquire Knowledge
Learning Python is essential for Data Science because, Python is preferred by over 80% of the data scientists and also due to the extensive math, ML, and data visualization libraries Python comprises such as Scikit-learn, matplotlib, seaborn, etc.
Learning ML libraries is the next step where you can learn different algorithms like Naïve-Bayes, K-Means, and many more.
Step 2 – Practice until perfection
Start working on your projects, be it, at work, or in your learning group. Participate in hackathons. What you could learn in 2-3 days of work in a hackathon is far more than years’ work on projects.
Participate in Kaggle Hackathons, competitions, and community projects which can help you emerge as an ML expert.
Step 3 – Work on Networking
By working on hackathons and community projects also help you build learn buddies and peers who are like-minded professionals and have the same aspirations as you.
This step helps in not just sharing knowledge but also helps in identifying various opportunities opening up in the data science field, getting tipped off on conferences being held, and more.
Step 4 – Mock Interviews/Interview Q&A
This step is where you are gearing up for the available opportunities. Prepare for the upcoming interviews by understanding the top interview question and answers, attending mock interviews held by hiring managers from Fortune 500 companies. Groom yourself, build your confidence levels, employ the best practices to nail the interviews held by top employers.
Step 5 – Job Placement
Finally, you are ready for D-day. With the help of the previous steps, your knowledge gaps are covered, your confidence is intact, you are all set to face the grueling interviews.
Generally, a candidate for the Data Scientist position has to undergo 3-4 stages of the interview where the first step is more likely to be a telephonic round, followed by the second step which could be a technical round, closely followed by a video call in the 3rd round and finally closing it with a cultural fit round which is more likely to be an in-person interview.
How to zero-down on the right institute for pursuing a Data Science course?
The two aspects that count while deciding on an ideal IT training provider are the curriculum and the training delivery. However, one should not ignore the other perks like placement assistance, the support they provide to help you emerge as a well-rounded data scientist, the grooming they provide to get you placed in the top companies.
Premium institutes like offer a comprehensive Data Science course that is comparable to a master’s in Data Science program offered by top universities in the USA.
What other professions in Data Science can one target?
While Data Scientists are the hottest and highest-paid professions of the 21st century, there are other suitable roles for beginners and the less experienced professionals who hope to be a part of the data science niche.
The following are the other career options in the data science niche:
- Data Analyst
- Data Engineers
- Machine Learning Engineer
- Data Architect
- Data Analytics Manager