- Design experiments, test hypotheses, and build models utilizing the traditional datasets and graph data.
- Apply advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems.
- Identify what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as geo-location or social media
- Utilize patterns and variations in the volume, speed and other characteristics of data for predictive analysis.
- Define the preprocessing or feature engineering to be done on a given dataset, data augmentation pipelines, training models and tuning their hyperparameters, analyzing the errors of the model and designing strategies to overcome them
- Selecting features, building and optimizing classifiers using machine learning techniques
- Extending the company's data with third party sources of information when needed
- Creating automated anomaly detection systems and constant tracking of its performance.
Qualification- Bachelor's in mathematics, statistics or computer science or a related field; Masters or PhD degree preferred.
Experience- 5+ years of relevant quantitative and qualitative research and analytics experience.
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