Job Description

Company Description: Bharti Airtel Limited is a leading global telecommunications company with operations in 18 countries across Asia and Africa. Headquartered in New Delhi, India, the company ranks amongst the top 3 mobile service providers globally in terms of subscribers. In India, the company\'s product offerings include 2G, 3G and 4G wireless services, mobile commerce, fixed line services, high speed home broadband, DTH, enterprise services including national & international long distance services to carriers. In the rest of the geographies, it offers 2G, 3G, 4G wireless services and mobile commerce. Bharti Airtel had over 423 million customers across its operations at the end of March 2020. This is a place where you\'re welcomed as your own perfectly unique self, and celebrated for the skills, talent, and perspective you bring to the team. : This is a very inspiring role in Networks Digitization team where you will use your knowledge and/or experience in Data Science methodologies and apply them to develop analytics based solutions that produce telecom Networks and customer experience use cases as well as quantitative and qualitative business insights. You will work in a highly collaborative environment where you communicate and plan tasks and ideas. Responsibilities and Duties: Responsible for developing scientific methods, processes, and systems to extract knowledge or insights to drive the future of applied analytics in Networks. Mine and analyze data from company databases to drive optimization and improvement of product development and business strategies. Assess the effectiveness of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to data sets. Use predictive modeling to enhance Network experience customer experiences, revenue generation and other business outcomes. Must be able to communicate effectively and have detailed knowledge of data preparation and cleaning, algorithm selection & design, results analysis, industrialization. Work with stakeholders to understand business requirements and processes for projects so implementation can be done without delays. Work with partners as necessary to integrate systems and data quickly and effectively, regardless of technical challenges or business environments. Qualifications and Skills: Solid understanding in Statistics, e.g., hypothesis formulation, hypothesis testing, descriptive analysis and data exploration. Good understanding in Machine Learning, e.g., linear/logistics regression discriminant analysis, bagging, random forest, Bayesian model, SVM, neural networks, etc. Strong programming skills in various languages (Python, PySpark , Scala, R) Strong ambition to learn and implement current state of the art machine learning frameworks such as Scikit-Learn, TensorFlow, and Spark. Familiarity with Linux/OS X command line, version control software (git). Familiarity in programming or scripting to enable ETL development Familiarity with relational databases and SQL .

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