Data Scientist
Tasks
- Adapt to changing project priorities
- Apply advanced techniques like time series, boosting algorithms
- Build automated model monitoring workflows
- Collaborate with stakeholders and cross-functional teams
- Create dashboards for model performance visualization
- Design and implement predictive and prescriptive models
- Develop and tune machine learning models using Python, PySpark, TensorFlow, PyTorch
- Operate in agile development cycles
- Write scalable and deployable code
Perks/Benefits
Skills/Tech-stack
Agile methodologies | Boosting algorithms | Dashboard tools | Dashboard tools like Databricks | Data Visualization | GenAI | LightGBM | Model Deployment | Model Distillation | Model Interpretability | Model Monitoring | Palantir | PySpark | PyTorch | Python | Retrieval-Augmented Generation | Series modeling | TensorFlow | Time Series | Time Series Modeling | Tools like Databricks | XGBoost
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