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- Industry
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Roles and responsibilities: The data scientist works closely with the stakeholders of the business to understand their goals and determine how data can be used purposefully to achieve the set objectives. They are the sole designers of data modeling processes, create algorithms and predictive models, extract the data the business needs and help in analyzing the data and share insights for the betterment of the business's decisions. This is the role that demands highly analytical skills to convert raw information or data into valuable business insights. The main responsibilities include identifying data sources, undertaking preprocesses of structured and unstructured data, building solutions and strategies to business challenges.
Average salary (per annum): US$1,15,825
Qualifications:
Data Science Specialization-JHU at Coursera: is an ideal mix of application and theory using R programming languages. This is provided by Johns Hopkins University. The curriculum includes the data scientist's toolbox, R programming, Getting and cleansing data, reproducible research, statistical inferences, practical machine learning, developing data products, and capstone.
Introduction to Data Science-Metis: prerequisites for this course are to have knowledge of Python, linear algebra, and some basic statistics. The curriculum includes computer science, statistics, linear algebra, short course, data modeling both supervised and unsupervised learning, and model evaluation. It also has advanced model evaluation and data pipelines and presentations included in the course for better understanding.
Applied Data Science with Python Specialization-Umich at Coursera: The course is launched by the University of Michigan, it gives a strong introduction to widely used data science Python libraries, like matplotlib, nltk, pandas, networkx pandas, networkx and scikit-learn unlearn and learn how to use them on real data. It includes applied plotting, charting & data representation in Python, machine learning, text mining, and social network analysis in Python.
Fractal Analytics: The company has emerged as one of the top analytics services service providers in the country. The company has a global footprint boasting of several Fortune 500 companies from industries like retail, insurance, and technology. It has many branches in all parts of India hiring new positions.
Amazon: Amazon is one of the biggest e-commerce companies around the world and is also among the top data science recruiters worldwide. Amazon relies on its data scientists for several core operations like supply chain optimization, fraud, and fake review detection, multivariate testing, inventory, and sales forecasting, advertising optimization, and HR analytics.
Deloitte: Deloitte is part of the Big Four, offering services like consulting, financial advisory, tax audit, and enterprise risk across the globe since 1845. Data scientists at Deloitte undertake several analytics projects which may be multidisciplinary in nature. Their responsibility is to simplify complex, and large data and ensure that it is easy to understand my clients.
LinkedIn: LinkedIn was one of the first companies to have a team of data scientists. Since it is a social networking service it allows its users to excel in their professional links. This also demands data interpreters to understand and enable businesses in making better decisions.
MuSigma: It is the largest solutions provider relating to science decisions and analytics. Data scientists here would involve analyzing data, tuning it, and making it simple for evaluating results. These results then are used to make crucial decisions in the organizations.
