Data Scientists are well-trained professionals whose responsibility and job description includes, collecting, analyzing and interpreting large amounts of data. The Data Scientist job description is a culmination of the work of a mathematician, scientist, statistician, and computer professional. Their job involves the usage of the most advanced analytical tools to interpret data and to present it in the form of meaningful information. To be a better data scientist, you must emphasize on Machine Learning, Data Mining, and forecasting outcomes. Data Scientist jobs are increasing at an exponential rate.
The Data Scientist Job Description
The duties of Data Scientists include analysis of data groups, formulation of statistical models, and the creation of complex predictive models through the usage of the upgraded statistical set tools. The Data Scientist job description can be advertised as a Machine level Architect and a Data Level Architect. According to Chirasmita Mallick, who works with G2 as a Data Scientist, Data Science is one of the four paradigms of science – The other three being the empirical, computational, theoretical sciences. Data Science or Data Science-driven insights are the fourth aspects of science.
Chirasmita also believes that Data Science is pretty multi-dimensional, because you, as a Data Scientist are unifying the knowledge of statistics and machine learning. Your curiosity in solving problems, how you connect dots together and extrapolating insights out of the data matters. Data Science is a combination of all these skills and a measure of how you can communicate the results of these tools and techniques. This forms the entire ecosystem of Data Science. The Data Scientist job description includes many activities and functions.
A data scientist’s job description focuses on the following –
- Automating the collection process and identifying the valuable data.
- Collection of large amounts of raw data facts and figures and converting them into a usable format.
- Use of data-driven techniques to solve business-related issues and problems.
- Look out for upgrades on analytical techniques.
- Act as a communication link between the business development and engineering team.
- Firm understanding of statistical tests and distribution.
Qualification and Required Skills for a Data Scientist Job
To complete a wide range of sophisticated analytical tasks in a real and short time, a Data Scientist should have a sound educational background, and should also have sufficient experience. Unlike other job requirements where the requirement specifies a particular qualification only, a Data Scientist’s job description requires a bachelor’s degree in technology or engineering. In addition to a bachelor’s degree, it also requires knowledge of various Programming Languages like (SQL, PYTHON), multiple data platforms like (HIVE, SPARK), and statistical computing language like (R). It also includes knowledge of Machine Learning and Networking.
Some other skills include –
- Data Visualization.
- Data Wrangling.
- Understanding of Analytical Functions.
- Knowledge of Unstructured Data analysis.
- Database (Relational Database Management System).
Analytical Knowledge of R and SAS – This helps a Data Scientist extract data from unstructured data, and find useful stats from chunks of other data. Other than these technical skills, some non-technical skills also play an important role –
- Knowledge of Business.
- Awareness of new technology.
- Communication Skills.
- Adaptability and Flexibility.
Data Scientist Job Profile
Data scientist jobs include the following profiles – Machine Learning Engineer, Data Architect, Data Analyst, Data Administrator, Data Scientist, Data Manager, and Business Intelligence Manager.
Machine Learning Engineer
A software engineer who is specialized in Machine learning. Their main job is to run machines with the help of Machine Learning libraries. The average salary according to Glassdoor is ₹1,092,085 per annum, for three to four years of experience in the field.
Professionals who maintain and design structured databases for a company. They define how data is stored and can be used effectively by different entities. Companies like Nokia, Samsung, and Apple hire these professionals on an ongoing basis. The average salary package is around ₹1,536,436 per annum, for four to five years of experience.
They collect data (sales figures, market research, logistic data) from different sources and translate them into very simple language for further use and making business decisions. The average salary for an entry-level data analyst is ₹350,000 per annum.
Business Intelligence Manager
The role of a business intelligence manager role is highly analytical and requires a balance of IT, communication and problem-solving skills. They transform data into insights that helps managers, and executives, to make better decisions. The average salary is ₹1,299,443 per annum, for five to nine years of experience.
A Data Administrator is a specialized professional who maintains the database of a company, and also keeps data secure from all frauds. The average salary in India is around ₹770,055, per annum for three to four years of experience
With the motive of increasing profits and not using data just for statistical representation, organizations desired a new type of professionals who were going to be trendsetters. This new breed of experts was not only expected to have knowledge about predicting and presenting the hypotheses of data but also required to be team players and programmers. Many online learning platforms have now added new programs to accommodate this requirement, and train technology professionals to become a Data Scientist. Exponential growth in data scientist jobs can be seen all over the world in different industries & at all levels of organizations. Financial and insurance companies are hiring a large number of Data Scientists as well, and the Data Scientist job description is coveted, to say the least.
Why should you aspire to be a Data Scientist?
According to Forbes magazine “The Sexiest Job of the 21st Century” is that of a data scientist. The United States of Labour Statistics forecasted that the total demand for Data Scientists is expected to increase by 19% by the year 2026, which is faster than the average of all other professions. The rapid growth in data collection has increased the demand for data scientists for heightened Data Mining. As per job portals like Dice and Indeed, there has been an overwhelming increase of 400% in the demand for Data Science from 2013, and as much as 29% over the last. As per research by Accenture, 88% of companies in India are planning to invest in AI and machine learning. According to Indira Krishnamoorti, a Senior Data Scientist at Brillio, and a mentor at Springboard, there are two main reasons for this rise.
First and foremost, organizations pile up a humungous amount of data on a day to day basis. This data comes from various sources but is rendered useless as long as it has not been seen from the eyes of a Data Scientist. Data Scientists make sense out of this data and add value to the organizations they are working for, by interpreting this data, and drawing useful patterns and insights from it. This brings about sales and growth for the organization. The second reason is, although there is a huge demand for Data Scientists, there is a shortage of skilled Data Science professionals today – There are more Data Scientist jobs than Data Scientists! There is a huge demand-supply gap, and that is one of the biggest reasons why there is a huge demand for Data Scientists.
- A Data Analyst’s job description includes investigating various insights. You can always find some ways to summarize data, and then present it in an insightful manner – with various dashboards or reports for senior management teams and marketers.
- A Data Analyst should not only build new algorithms or work on a huge amount of data but also know some forms of querying, such as R and Python programming, as well as Tableau or Power BI – for dash-boarding purposes.
- Use of Mathematical skills like matrices, calculus, and various statistical techniques.
- Use of Programming skills like Python, R, Pig, Hive, Hadoop, MapReduce, SQL, and NO SQL.
How much is Data Scientist Salary?
Not only is the data scientist job description attractive, but Data Scientist jobs are also lucrative. According to Glassdoor’s research, an entry-level job profile pays a good salary. The average entry-level salary of a Data Analyst is around Rs.4,50,000/- per annum, and senior-level Data Analyst salaries range from Rs.500,000 to Rs.10,00,000/- per annum. Some giant MNC’s offers a wide range of salaries in India. Let us look at the salary range levels as per different levels of experience –
|Data Scientist |
|Average Salary||₹8-10 LPA|
|5 to 10 years||₹10-20 LPA|
|10 + years||This can vary; depends on the expertise one may have|
According to Glassdoor, the average salary of a Data Scientist is around $113,436 per annum (On a Global Scale).
Real-Time Example of the Use of Data Science – Predictive Maintenance Strategy
Data Scientists explore a variety of fields and use Data Science accordingly. One example is the use of Predictive Maintenance Strategy by Data Scientists to take care of failed equipment and optimize oil production. In old oil wells where inefficiency is the reason for the subpar performance of oil wells, well operators know about the crucial stages of the shutdown and various maintenance periods. This is only possible by collecting data from different sensors and based on historical data. Using this history, they can predict machine failure stages and can prompt operators for maintenance – which will avoid hazardous situations. Thus, oil overflows, sudden downtime and oil losses are saved in time. In addition to this, there are several use cases like- data science in pharmaceutical industries, predictive modeling for maintaining oil and gas supply, data science in biotech, data science in education, and others.
Thus, one can see the grandeur of this branch of science, which is restricted not only to mathematics or programming, but also requires sectoral knowledge. You can pick a sector and study the trends in that particular industry. The retail industry relies heavily on insights from data. Marketing and operational decisions are formulated based on the data collected by various tools.
Without the expertise of a Data Scientist, the latest available set of tools that provide insights would render sets of data as insufficiently used – The role of a Data Scientist is paramount in the extraction of useful information from sets of data. In the context of present-day scenarios, Data Scientists are required in all fields of an economy. To become a professional in the field of today and tomorrow (Data Science!), read and gauge your interest through various courses.
Now that you know about the data scientist job description, are you interested in learning Data Science? At Springboard, you can get a wide range of online courses in Data Science, Artificial Intelligence, and Machine Learning. Real-world projects, Mentorship from experts, and several fascinating features will help you achieve your dream of becoming a Data Scientist.