Data Scientist - Delhi/NCR (0-2 Years Of Experience)

Job Description and Responsibilities: Working in a small team led by the Chief Risk Officer and the co-founder of company, the data scientist will work on improving the data science capabilities. We currently have 2 key models, admit predictor model and the employability assessment model, and the selected candidate will work on improvising the same. The admit predictor model helps students shortlist the colleges they should target for higher studies. The employability assessment model helps lending partners make better offers to students who want to pursue higher studies. The ideal candidate can think big picture, and is comfortable with getting his/her hands dirty with data. The candidate should be resourceful in getting the data needed to support one's hypothesis. Prior experience through internships / job experience / Kaggle contests would be highly valued. The candidate should understand that in the real world data is never clean and data collection / data gathering is a significant part of the daily job requirements. Do you appreciate the difference between causation and correlation- If you answered yes, can see through the hype of Big Data, and know when to use an OLS and when to use GBM, we want you here! Qualification: Prior experience working on data science projects Experience in NLP will be preferred Job Description and Responsibilities: Working in a small team led by the Chief Risk Officer and the co-founder of company, the data scientist will work on improving the data science capabilities. We currently have 2 key models, admit predictor model and the employability assessment model, and the selected candidate will work on improvising the same. The admit predictor model helps students shortlist the colleges they should target for higher studies. The employability assessment model helps lending partners make better offers to students who want to pursue higher studies. The ideal candidate can think big picture, and is comfortable with getting his/her hands dirty with data. The candidate should be resourceful in getting the data needed to support one's hypothesis. Prior experience through internships / job experience / Kaggle contests would be highly valued. The candidate should understand that in the real world data is never clean and data collection / data gathering is a significant part of the daily job requirements. Do you appreciate the difference between causation and correlation- If you answered yes, can see through the hype of Big Data, and know when to use an OLS and when to use GBM, we want you here! Qualification: Prior experience working on data science projects Experience in NLP will be preferred