The scope of Job opportunities in data science is rising exponentially

Since the past couple of years, data science has been gaining more industry-wide recognition owing to its vast scope of applications. Hence, it is no wonder that data science jobs are increasing every day. Further, data science jobs are the highest paid in the IT industry. The U.S. Bureau of Labor Statistics reports that the demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026. Data Science is more like an umbrella term. This branch includes several scientific methods, math, statistics, and other tools to analyze and manipulate data on a variety of models and raw data to get information. Therefore, there is a diversity of career opportunities in this sector.

However, irrespective of the job roles, there are some key skills one must have if you're seeking a career in this field. These include,

• Knowledge in a programming language, like R or Python, and a database querying language like SQL.

• Good understanding of statistics topics like statistical tests, distributions, maximum likelihood estimators and mathematical concepts viz, Derivatives And Gradients, Step Function, Sigmoid Function, Logit Function, Relu (Rectified Linear Unit) Function, Cost Function (Most Important), Plotting Of Functions, Minimum And Maximum Values Of A Function, Scalar, Vector, Matrix And Tensor Functions, Multivariable Calculus & Linear Algebra

• Familiarization with machine learning algorithms like k-nearest neighbors, random forests, ensemble methods, and more.

• Incredible Data Intuition, Data wrangling, Data Visualization

• Have a knack for critical thinking, problem-solver attitude, intellectual curiosity and strong command on communication.

Building grounds on what that has already been written and said, Analytics Insights compiles the list of the top Data Science jobs for November.

Data Engineer

(Average salary: INR 7,73,718)

Range: INR 338K- INR 1,568K

Data engineers are mainly responsible for transforming data into a format that can be easily assessed. They work closely with data scientists and are primarily in charge of architecting solutions for data scientists that let them do their jobs efficiently. A data engineer must have an understanding of how to optimize data retrieval and how to develop dashboards, reports and other visualizations for stakeholders.

Machine Learning Engineer

(Average salary: INR 7,83,336)

Range: INR 349K- INR 1,573K

They design self-running software to automate predictive models. They infuse the laws and rules of the Data Science world with that of programming to help organizations reap the full benefits of AI/ML technologies while adhering to the standard programming practices and protocols. Also, this is an emerging role; not many IT specialists have direct experience with it.

Data Scientist

(Average salary: INR 9,94,974)

Range: INR 400K- INR 1,892K

Typically, a day in data scientist's job includes asking questions and locating potential avenues of study, with less concern for specific answers and more emphasis placed on finding the right question to ask. Data scientists accomplish this by predicting potential trends, exploring disparate and disconnected data sources, and finding better ways to analyze information. By using a combination of programming, statistical skills, machine learning algorithms, data scientists can excavate through large amounts of structured and unstructured data to identify patterns.

Data Analyst

(Average salary: INR 5,50,000 )

Range: INR 277K- INR 1,097K

Data analysts examine information using data analysis tools and help their teams develop insights and business strategies. They do this by collecting, processing and performing statistical analyses on a large dataset. They also aid in the decision-making process by preparing intelligent reports to communicate trends and insights.

Data Architect

(Average salary: INR 18,53,248)

Range: INR 1,061K- INR 3,262K

The data architect visualizes the complete framework and creates the blueprint for data management systems. They investigate a company's current data infrastructure and potential data sources (internal and external), then design a plan to integrate, centralize, protect and maintain them. They also integrate current systems with a desired future state.