Turn complex data into actionable recommendations that can improve our business. You will track our business goals, find the root of operational issues, and find new ways to enhance our products. Our vision is defined through an interdisciplinary approach to research, merging contributions from computer, web science, machine learning and statistics, and addressing numerous applied problems.
The teamwork on the developing methods, algorithms, and ultimately computer programs for making reliable inferences from high dimensional and heterogeneous data. Comviva data science research program is centered on the disciplines to semantically integrate and enrich data, to model and understand data, to design and analyze scalable computational approaches to machine learning, and to build systems that allow storing and processing vast amounts of data. Ultimately our research enables new and improved applications to emerge, in a multitude of domains.
Purpose and Challenges
The purpose of Data Science, we conclude that Data Scientists are the backbone of data-intensive companipt. The purpose of Data Scientists is to extract, pre-process and analyze data. Through this, companies can make better decisions. Various companies have their own requirements and use data accordingly. In the end, the goal of Data Scientist to make businesses grow better. With the decisions and insights provided, the companies can adopt appropriate strategies and customize themselves for enhanced customer experience.
- Find patterns within data and draw insights from the data
- Scrutinize and predictions from the data
- Assist teams in making smarter business decisions.
- Helps the company in the right direction
- Data Science for Customer Acquisition
- Data Science for Better Marketing
- Bring Innovation and enriching lives
Learning & Growth
In a knowledge-worker organization, people — the only repository of knowledge are the main resource. In the current climate of rapid technological change, it is becoming necessary for knowledge workers to be in a continuous learning mode. In any case, learning and growth constitute the essential foundation for success of any knowledge-worker organization.
- Creating an organic thirst for learning is a part of our culture and we are committed to our employees’ professional development
- Agile learning practices
- Mobile enabled learning practice
- Learning programs are built around employees’ priorities
- Invest in employees’ career development and give them a chance to keep updating their skills and knowledge