Senior Data Scientist
Tasks
- Apply statistical predictive and prescriptive modeling
- Build forecasting models
- Build production grade data science solutions
- Collaborate across data engineering analytics and product teams
- Design and implement causal inference methods
- Develop and deploy machine learning models
- Develop optimization approaches for planning and allocation
- Embed causal reasoning into decision systems
- Integrate generative AI into data science workflows
- Integrate models into scalable APIs and platforms
- Monitor and manage deployed models
- Validate modeling approaches across teams
Perks/Benefits
- Career advancement
- Hybrid work
- International mobility
- Learning and development
- Professional development programs
- Remote work
- Training
Skills/Tech-stack
APIs | AWS | Agent systems | Airflow | Apache Spark | Azure Machine Learning | BigQuery | Causal Inference | Cloud Computing | Cloud platform | DBT | Data Pipelines | Databricks | Experimentation | Forecasting | Generative AI | Google Cloud | Google Cloud Platform | Language Models | Large Language Models | Lifecycle Management | Machine Learning | Microsoft Azure | Model Lifecycle | Model Lifecycle Management | Model Monitoring | Optimization | Probabilistic Forecasting | Python | RAG | Retrieval-Augmented Generation | SQL | Snowflake | Statistical modeling | Time Series | Uplift Modeling
Education
N/A
Roles
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