Brief description :
Roles and Responsibilities
1. 5+ years’ experience solving analytical problems using quantitative approaches. Experience in SQL or other programming languages.
2. Advanced degree in Computer Science, Engineering, Math/Statistics, Physics, Economics, or equivalent practical experience.
3. Multiple years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models.
4. Experience in python and tableau will be an added advantage
Understanding of statistics (e.g., hypothesis testing, regressions, ML systems).
Practical understanding and hands-on experience with regression modelling (linear and logistic)
Experience communicating the results of analyses with product and leadership teams to influence strategy.
Direct experience with both supervised learning methods (linear and logistic regression, time-series modelling, generalized linear models, decision trees, random forests, support vector machines, etc.) and unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components).
Direct experience analyzing A/B experiments
Proven ability to convey rigorous technical concepts and considerations to non-experts
The ability to drive impact and be a true partner to the business, working closely with top-level managers
Should have good understanding of Modeling techniques and methods
Should have excellent analytical and presentation skills
Excellent written and verbal communication, including technical writing skills