Data Scientist & Business Development at Grid Logic Software Private Limited
We are looking for individuals who can turn data into information, information into insights and insights into business decisions.
You will be working on unique data consisting of around 1000 events per day. You will continuously drive data culture and evangelize use of data science in all possible aspects of business.
You will make sure that product is having end to end data points for partners and all stake holders to required information to grow the business.
Researching and developing algorithms/ models/ strategies for personalizing the product. Make sure developed algorithms drive significant lift in reality and refine as required
Help building ML/predictive framework to draw insights at scale for different aspects of business, for example understanding drivers of various customer behaviour or understanding points of failure
Develop strategies for effective data analysis and reporting
Help build and enhance sophisticated algorithms and various analytical tools to transform raw data into actionable business insight
Preparation and analysis of performance reports
Monitor the success of the clients and advise them by applying industry knowledge to interpret data and improve performance
Keep abreast of industry news and trends
Knowledge, Skills & Experience:
Excellent problem solving skills, with ability to communicate even complex ideas in succinct manner
Proven experience as a data scientist or data analyst
Strong work ethics like sense of collaboration and ownership, result orientation, being team player
Understanding of Python, Tableau, Power Bi, related tools used from data handling to modelling to implementation is preferred
Master or equivalent degree in Computer Science, Mathematics, Statistics and Information Systems.
Knowledge in SQL & Java script is a huge plus
Ability to display complex quantitative data in a simple, intuitive format and to present findings in a clear and concise manner
Understanding in machine learning, general statistics and data science principles
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