Data Science is the latest buzzword in the industry and is the most thrilling and rewarding job role. The expertise in the field, the Data Scientists, not only enjoy high remunerations but also get the opportunity to bring a direct business impact. Data Science has applications across industries starting from consumer behavior analytics in Retail and E-commerce to computer vision applications such as detection and classification of objects and humans.
Today, the current market size for data science is $38 billion. The market size in 2025 is expected to reach $140 billion. India is the second-highest country next to the US to have generated the demand to recruit about 50,000 Data Scientists for 2020 and 2021.
So, let’s see what Data Science is all about:
In simple terms, Data Science is an amalgamation of Statistics, Computer Science, and specific domain knowledge. Data Science is a diverse field that starts with simple data reporting activities to advanced predictive modeling using Artificial Intelligence.
Role of a Data Scientist:
- Gathering and analyzing data
- Processing and cleaning the data
- Integrating and storing data
- Applying data science techniques, such as machine learning, statistical modeling, and artificial intelligence
- Exploratory Data Analysis
- Choosing potential models and algorithms
- Measuring and improving results
- Presenting the results to stakeholders and making adjustments based on the feedback
Data Science based roles:
- Data Scientist – Works on complex and specific problems to bring non-linear growth to the company. For example, making a credit risk solution for the banking industry or use images of vehicles & assess the damage for an insurance company automatically.
- Data Engineer – He/she would implement the outcomes derived by the data scientist in production by using industry best practices. For example, Deploying the machine learning model built for credit risk modeling on banking software.
- Business Analyst – Helps in running the business smoothly by assisting the management to make data-driven decisions on a day-to-day basis. This role would be communicating with the IT side and the business side simultaneously.
Again, there are a lot of other roles under the data science umbrella such as data analyst, statistician, data analytics manager, MIS professional etc.
Essential Data Science Skills:
- Statistical analysis: Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.
- Machine learning: Implement algorithms and statistical models to enable a computer to automatically learn from data.
- Computer science: Apply the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering.
- Programming: Write computer programs and analyze large datasets to uncover answers to complex problems. Data scientists need to be comfortable writing code working in a variety of languages such as Java, R, Python, and SQL.
- Data storytelling: Communicate actionable insights using data, often for a non-technical audience.
Tools you must master for Data Science:
- Microsoft Excel: Excel prevails as the easiest and most popular tool for handling small amounts of data.
- SQL: SQL is one of the most popular data management systems which has been around since the 1970s and has been the primary database solution for a few decades.
- Python: This is one of the most dominant languages for data science in the industry today because of its ease, flexibility, open-source nature. It has gained rapid popularity and acceptance in the ML community.
- Tableau: It is amongst the most popular data visualization tools in the market today. It is capable of handling large amounts of data and even offers Excel-like calculation functions and parameters. Tableau is well-liked because of its neat dashboard and story interface.
Data scientists play a key role in helping organizations make sound decisions. As such, they need “soft skills” in the following areas.
- Problem-Solving skills – The knowledge of statistics and computer science can be achieved by studying but it is the domain knowledge along with the problem-solving skills that will help you become a long shot. A majority of companies start their data science recruitment with problem-solving tests. You don’t need to be a master at it but a curious mind will help you in forming this skill.
- Structured Thinking – The ability to structure your thoughts and map out each of them is certainly a must-have skill. Structured thinking is made of use in the initial steps of the project where the problem statement and hypothesis are to be formulated.
- Storytelling Skills – A key skill that all the data science and analytics professionals must have is the ability to express the data in a format that is understandable by the stakeholders – a story. It is this step that requires creativity and human skills.
According to Glassdoor, the average pay scale of a data scientist is Rs. 900k per year in India whereas the average salary of a computer programmer is Rs. 400k per year.
Data Science is evolving at a lightning speed and that’s what makes the role of a data scientist so exciting.
Reference: Analytics Vidhya
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