This article has been written by Shivang , one of our highly dedicated and hardworking volunteer.
“By the year 2020, about 1.7 megabytes of new information will be created every second for every human being on planet”, a line from a article in Forbes that you will find quoted in almost every other article related to data science. Words like Data Science and Big Data have become a buzzword today but there is very less clarity related to these terms. This article will focus on the actual meaning of data science, skills required, payscale ,the downsides of the profession and application of data science in Actuarial Science.
Data Science is a multidisciplinary field which involves techniques, algorithms and methods from the fields of mathematics, statistics and computer science, used to analyze structured and unstructured data for explanatory and predictive purposes. A very basic practical example of application of data science may be a shopping website recommending its customers products based on their purchase history.
Many a times it is used interchangeably with data analyses and business intelligence. However, in its true sense it is more predictive than explanatory. It analyses patterns in the data sets to predict future values rather than explaining and making reports out of data.
- Statistics- Data Scientists need to have strong knowledge of statistics and statistical tools. They need to posses knowledge of Descriptive and Inferential Statistics as well as Probablity.
- R Programming- R is one of the most powerful tools built to solve statistical problems. About 43% of data scientists today use R.
- Python Coding- Python due to its versatility is the most common coding language used by the data scientists
- SQL- It is a database management programming language that can help you to carry out operations like add, delete and extract data from database.
Other equally important skills that one needs to posses are-
- Hadoop Platform
- Machine Learning and AI
- Data Vizualisation
According to payscale.com the median salary of a data scientist is around Rs.6.21lpa.The entry level salaries range from 2.5 lpa to 3 lpa rising upto 20 lpa at a very high experience level.
Downsides of the Profession
Many a times managers hire data scientists with a lack of clarity of purpose and goals.As a data scientist, you need the whole picture. You need to know what your goal is because otherwise you can’t expect to achieve it. Unfortunately, people often narrow that goal with their own theories before presenting it to you.They tend to overestimate (give them ultimate answers to questions) or underestimate (expect making reports and analyses). Data scientist also complain of not being the descision maker. Data science provides suggestions, advices. Usually it’s not decision making role. And many data scientists get frustrated when decision makers follow their instincts ignoring facts.
Application of Data Science in Actuarial Science
Actuaries are always dealing with data and making inferences out of it. However they had been always dealing with the structured data. With technological advancements we are able to collect, store and analyze large amounts of unstructured data. Actuaries are using such data from customers available from social media, wearables, IOT etc. apart from the information provided by them to provide more flexible and customized policies and pricing with the help of data science techniques.