Job Description:
- Contribute and build an internal product library that is focused on solving business problems related to prediction & recommendation.
- Research unfamiliar methodologies, techniques to fine tune existing models in the product suite and, recommend better solutions and/or technologies.
- Improve features of the analytics product to include newer machine learning algorithms in the likes of product recommendation, real time predictions, fraud detection, offer personalization etc
- Collaborate with client teams to on-board data, build models and score predictions.
- Participate in building automations and standalone applications around machine learning algorithms to enable a – One Click- solution to getting predictions and recommendations.
- Analyze large datasets, perform data wrangling operations, apply statistical treatments to filter and fine tune input data, engineer new features and eventually aid the process of building machine learning models.
- Run test cases to tune existing models for performance, check criteria and define thresholds for success by scaling the input data to multifold.
- Demonstrate a basic understanding of different machine learning concepts such as Regression, Matrix Factorization, K-fold Validations and different algorithms such as Decision Trees, Random Forrest, K-means clustering.