Data Science

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data. Data scientists use a variety of tools and techniques to collect, clean, analyze, and visualize data. They also use statistical and machine learning models to make predictions and recommendations.

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Becoming a Data Scientist: Helpful Tips

Math, Stats, CS

Consider university or college courses for in-depth learning of data science tools and techniques

Master Data Science

There are many online resources and tutorials available on data science tools and techniques.

Build Data Experience

Build experience through personal projects, open source contributions, or data science internships.

Connect Data Scientists

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What Is The Earning Potentials For A Data Scientist?

Data scientists are highly sought-after, with salaries matching expertise. In a nutshell, the average data scientist’s salary in India as per experience can be summarized as follows:

Freshers (0-1 year)₹ 5.11 LPA
Junior data scientists (1-4 years)₹ 8.06 LPA
Mid-level (5-9 years)₹ 13.67 LPA
Expert (10-12 years+)₹ 24 LPA

Here are some of the things that data scientists can do

Here are some specific examples of the types of projects that data scientists might work on:

- Developing a machine learning model to recommend products to customers on an e-commerce website.
- Building a predictive model to forecast the demand for energy in a city.
- Analyzing data from clinical trials to identify new drug targets.
- Using data to improve the efficiency of a manufacturing process.
- Detecting fraud in financial transactions.
- Predicting the risk of customer churn.

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Identify patterns and trends in data

Data scientists use their skills in statistics and machine learning to identify patterns and trends in data that would be difficult or impossible to see with the naked eye. These insights can be used to improve products and services, make better business decisions, and even predict future events.

Build predictive models

Data scientists can build predictive models to forecast future outcomes. For example, they might build a model to predict customer churn, identify fraudulent transactions, or forecast the demand for a new product.

Develop and implement machine learning algorithms

Data scientists can develop and implement machine learning algorithms to solve a wide range of problems, such as image recognition, natural language processing, and fraud detection.

Communicate insights to stakeholders

Data scientists need to be able to communicate their findings to stakeholders in a clear and concise way. This often involves creating data visualizations and dashboards, as well as writing reports and presentations.