Data Scientist has become one of the most demanded jobs of the 21st century. It has become a buzzword that almost everyone talks about these days. Data Science is about extraction, readiness, examination, perception, and maintenance of data. It is a cross-disciplinary field that utilizes logical strategies and procedures to draw bits of knowledge from information.
A Data Scientist, specializing in Data Science, not only analyzes the data but also uses machine learning algorithms to predict future occurrences of an event. Therefore, we can understand Data Science as a multidisciplinary field that combines mathematics, statistics, and computer science.
Why Data Science?
Data Science is now the fuel of many industries. It is a new power that helps companies to grow and foster their businesses as they require data to perform and to make decisions. They drive meaningful insights from the data to improve the organizations to analyze themselves and their companies performance in the market.
Apart from the commercial sector, the healthcare sector also uses Data Science through which the doctors are now able to detect cancer and tumors at an early stage using Image Recognition software.
What is Data Scientist?
Data researchers are another type of analytical information specialist who has the specialized aptitudes to solve complex issues – and the interest to investigate what issues should be comprehended.
Why build a career in data science?
All sorts of businesses today invest in data science and analysis to make better decisions for both themselves and their customers. Data scientists have become an asset to most companies and teams.
Scope of data science
- In India, significant sectors like healthcare, pharmaceuticals, banking, telecommunications, e-commerce, and media require data scientists.
- India is second only to the US when it comes to data science jobs. 1 out of every 10 data science or analytics jobs is accounted for by India. (Quartz India)
- According to Business Today, There are up to 50,000 data science job vacancies in India right now, which means plenty of opportunities for skilled job seekers to look forward to.
Demand for data science
- Currently, the biggest employer of data scientists in the banking and finance sector, comprising about 44% of total data science jobs. However, by 2020, India will create 39,000 more data science jobs spanning sectors like agriculture and aviation. (Business Today)
- Evolving technologies mean that data science will see significant demand in fields, for instance, AI, cybersecurity, space exploration, and driverless transportation too. (The Economic Times)
Data science courses and certifications
Here is a list of some popular data science courses and certifications.
Website: Coursera/University of Michigan
Price: INR 3,474 per month
Learning Duration: Self-paced (Approx. 5 months)
Course: Intro to Machine Learning
Learning Duration: Self-paced (Approx. 6 months)
Course: Data Analyst in R
Learning Duration: Self-paced
Price: INR 12,480
Learning Duration: Self-paced
Price: INR 2,765 per month
Learning Duration: Self-paced (2 months approx.)
Website: Coursera/John Hopkins University
Course: Data Science Specialization
Price: INR 3,474 per month
Learning Duration: Self-paced (8 months approx.)
Course: The Data Science Course 2019
Price: INR 12,800
Learning Duration: Self-paced
Course: Introduction to Machine Learning
Price: Subscription-based (INR 2020 per month for 247 courses)
Learning Duration: 6 hours
Read the best books for Data Science
Statistics and Probability Books
- Naked Statistics by Charles Wheelan
- Introduction to Statistical Learning by Gareth James
- Introduction to Probability by Charles M. Grinstead
- Practical Statistics for Data Scientists by Peter Bruce
Books on Programming Languages and Tools
- Python Crash Course by Eric Matthes
- Introduction to Machine Learning with Python by Andreas Muller
- Hands-on Programming with R by Garrett Gorlemund
- Learning SQL by Alan Beaulieu
- Hadoop- The Definitive Guide by Tom White
- SQL Cookbook by Anthony Molinaro
- Learning SQL by Alan Beaulieu
- Practical Data Science with R by Nina Zumel
There is various influencer which can be followed, as the insight and the knowledge they share can be useful to aspiring Data Scientist or the existing professionals. Some of these influencers are:
- Andrew Ng: He is a prominent name among Data science thought leaders. He is a professor at Stanford University and the co-founder of Coursera.
- Kirk Borne: He is the principal data scientist and executive advisor at the Booz Allen Hamilton since 2015.
- Lillian Pierson is a big name among the best big data influencers.
- Naval Ravikant is the co-founder and CEO at AngelList.
- Evan Sinar is the Vice President and also the main data scientist at Development Dimensions International (DDI).
Data scientists salaries
Average data scientist job salaries can vary according to skills and experience. Therefore, the annual average wage data for data science and related job roles are as follows:
|JOB ROLE||AVERAGE ANNUAL SALARY||SALARY RANGE (LPA)|
|Data Scientist||6.3 Lakhs||3 – 20|
|Data Analyst||4.9 Lakhs||1.9 – 8.2|
|Data Engineer||5 Lakhs||3.4 – 2|
|Business Analyst||5.8 Lakhs||2.5 – 10|
|Machine Learning Engineer||7 Lakhs||3.2 – 20|
|Statistical Analyst||5.8 Lakhs||1.9 -10|
Data source: AmbitionBox
Skills Required to be a successful Data Scientist
Here are a few necessary skills required to be a data scientist:
- Strong problem-solving skills with an emphasis on product development.
- Experience using statistical computer languages, for example, R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques, for instance, clustering, decision tree learning, artificial neural networks, etc.) and their advantages and disadvantages.
- Above all, Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
- Critical thinking
- Business sense
Qualifications Required to Become Data Scientists
If you earn a Bachelor’s degree in Computer Science and get certification in BigData/Data Analytics then you can join as a Data Scientist or Engineer intern or employee at a firm
If you earn a Bachelor’s and/or Master’s degree in Applied Mathematics or Statistics and complete online courses in Programming languages and Data Science/analytics then you can apply for jobs in Data science
Similarly, if you earn a Bachelor’s degree in Physics and take online courses in Programming languages and collect professional certifications in Data Science and Machine Learning or get a job as a Data Scientist or Machine Learning Engineer.
Why Choose a Career as a Data Scientist?
|High in demand||It’s a blurry term|
|Abundance of positions||The problem of data privacy|
|Highly-paid career||A large amount of domain knowledge required|
|Versatile||Mastering Data Science is near to impossible|
|Highly prestigious||Arbitrary data may yield unexpected results|
Responsibilities for the role of a Data Scientist
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data accuracy
Types of Data Scientist
A Data Scientist gets assigned with different names or designations in different organizations. According to data science central, there are 400 different designations assigned to them. For instance, a marketing company requires a statistician to get in-depth knowledge.
Data Scientist as:
- Data Engineers
- Machine Learning Scientists
- Actuarial Scientist
- Business Analytic Practitioners
- Software Programming Analysts
- Spatial Data Scientist
- Digital Analytics Consultant
- Quality Analyst
Tools used by data scientists
|Data Scientist||Apache Spark, Apache Pig, Hadoop, Apache Storm, Rapid Miner, Network X, etc.|
|Data Analyst||Excel, Pandas, Bokeh, Spotfire, etc.|
|Data Engineer||Hive, Mesos, H Base, Scala, etc.|
|Machine Learning Engineer||DataRobot, Tensor, Flow, BigML, etc.|
Now that we know a lot about Data scientist, we need to look for a job role which can help us build a career in this field.
That’s when the role of Vasitum comes into play, in finding appropriate Data Scientists Jobs
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Since this career portal is a new initiative, the chances of your application getting noticed at the top are high. It also provides you with a feature of messaging the recruiter, and the best part is everything comes for FREE. Its intelligent system shows you the exact job opportunities that suit you — no beating around the bush, but just meaningful jobs.
Now, as we know that we can find Data Scientist jobs, so we will now proceed further by looking at some of the tips to get a data scientist job.
- Master your mathematical and statistical skills
- Work on various data scientist assignments
- Deep knowledge of programming languages such as python, R programming, etc.
- Presently, there is a wide variety of courses and certifications available both online and offline so as to increase one’s chances of employment with high perks in this particular field.
- Organizations these days are ready to hire people who can actually provide valuable inputs that can help in strategizing various policies. One should know how to use their analysis in proving credibility to the company.
Basic Data Science Interview Questions asked
- What is Data Science?
- List the major differences between supervised and unsupervised learning?
- So, what are the important skills that are must in python with regard to data analysis?
- Describe selection bias and its types?
- Explain exploding gradients?
- Describe the SVM machine learning algorithm in detail?
- What are the support vectors in SVM?
- Can you share an incident where you helped in turning around the project?
Questions You Should Pose to the Interviewer
- So, will you be able to share with me the ventures I will get the opportunity to work upon if I get hired?
- I hope you got an opportunity to know more about me and my range of abilities well. By chance, if you have any more inquiries or any doubts about my capabilities, I hope we can examine and address that?
- Last and most important do not forget to negotiate your salary package and remember not to agree on a small package?
Now that you are through with the Interview and you have been offered a position as a Data Scientist, you should know the art of salary negotiation, especially when you are an aspiring data scientist.
Therefore, Salary negotiation is nothing but a designed series of talks between the employer and the exceptional employee about the package that both the parties agree on.
Points to remember while negotiating salary:
- Set yourself a baseline, but be determinant.
- Research the average salary for the position.
- Never ever quote the salary before the recruiter or the hiring manager.
- Drain out maximum information from the recruiter before you reveal your expectations.
- Smile is the basic but most important aspect while making a negotiation so that you don’t look nervous.
Negotiation is an art which also requires skills. However, It cannot be mastered at the first, it needs practice. Don’t make it a number game but focus more on your self-value. You will never be able to get paid what you deserve by avoiding negotiation.