MINIMUM QUALIFICATIONS & EXPERIENCE :
- 4-11 years of rich experience in implementing Machine/Statistical Learning solutions to complex business problems at scale
- Rich experience in various Machine Learning techniques like Regression, Classification, Ensemble of Decision Trees (Bagging, Boosting, Random Forest etc.), Support Vector Machines, Artificial Neural Networks, Clustering, Dimension Reduction etc.
- Intermediate-level proficiency (coding, scripting and prototyping skills) in Python or R
DESIRED QUALIFICATIONS & EXPERIENCE:
- Bachelors/Master's degree in Computer Science OR Master's degree in Statistics/Economics/Business Economics/Econometrics/Operations Research
- Experience in implementing the advanced techniques/methods like Recommender Systems (Collaborative Filtering, Matrix Factorization etc.), Association Rule Learning, Convolutional Neural Network, Recurrent Neural Network, Natural Language Processing (NLP), Reinforcement Learning (RL), Time-series Analysis and Bayesian methods
- Experience in productionizing the machine learning models for analytics-based SaaS (Software as a Service) products
- Familiarity with A/B site testing and evaluation
- Expert-level proficiency (good coding, scripting and prototyping skills) in Python or R or both
- Fair understanding of distributed computing in clusters, especially using R/Python
- Knowledge and familiarity with the Big Data stack: Hadoop, Hive, Spark, Map Reduce and other Big Data tools and technologies
- Operating knowledge of cloud computing platforms (AWS, especially EMR, EC2, S3, and AWS CLI)
- Understanding of database management systems like those of RDBMS, NoSQL, MongoDB etc.
- Knowledge of one or more domains: Telecommunication, Consumer Electronics, CPG, Online Media, BFSI, Healthcare, Logistics, Manufacturing etc.
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