Tasks:
- * Build pricing optimization and user profiling models
- * Build reusable data analysis workflows
- * Deploy lightweight models in resource constrained environments
- * Design and validate statistical and machine learning models
- * Develop anomaly detection models
- * Develop behavioral prediction and demand forecasting models
- * Evaluate and monitor production model performance
- * Extract insights from operational data
- * Productize analysis methods and models
- * Provide data inputs and validation benchmarks for simulation systems
- * Translate business needs into data tasks
- * Write analysis reports and business recommendations
Perks/Benefits:
Skills/Tech stack required:
[A/B] [A/B Testing] [Anomaly Detection] [B testing] [Causal Inference] [Clustering] [Data Analysis] [Data Pipelines] [Decision Trees] [Demand forecasting] [Hypothesis Testing] [Machine Learning] [Matplotlib] [Model Evaluation] [NumPy] [Operations Research] [Pandas] [Pricing Optimization] [Probability and statistics] [Python] [PyTorch] [Random Forests] [Regression Analysis] [Scikit-learn] [Seaborn] [Series analysis] [Simulation Modeling] [SQL] [Statistical modeling] [TensorFlow] [Time Series] [Time Series Analysis] [User Profiling] [XGBoost]
Educational requirements:
[Master's Degree]
Role(s):
[Algorithm Engineer] [Data Scientist] [Engineer] [Learning Engineer] [Machine Learning Engineer] [Scientist]