Senior Data Scientist

Tasks

• Apply statistical predictive and prescriptive modeling
• Build and maintain production grade data science solutions
• Build forecasting models for planning and operations
• Collaborate across data engineering analytics and product teams
• Design and implement causal inference methods
• Develop and deploy machine learning models
• Develop optimization approaches for resource allocation
• Embed causal reasoning into decision systems
• Ensure model explainability and business actionability
• Integrate generative AI into data science workflows
• Integrate models into scalable APIs and platforms
• Monitor and manage model lifecycle in production
• Review and validate modeling approaches across teams

Perks/Benefits

• Challenging projects
• Education program
• Events
• Free beverages
• Honest feedback
• Paid time off
• Private health insurance
• Wellbeing program

Skills/Tech-stack

Agent systems | Airflow | Amazon Web Services | Azure AI | Azure Machine Learning | BigQuery | Causal Inference | Cloud Storage | Cloud platform | DBT | Databricks | Decision Intelligence | Experimental Design | Experimental Methods | Forecasting | Generative AI | Google Cloud | Google Cloud Platform | Google Cloud Storage | Language Models | Large Language Models | Machine Learning | Model Deployment | Model Monitoring | Optimization | Probabilistic Forecasting | Python | Quasi Experimental | Quasi-experimental methods | RAG | Retrieval-Augmented Generation | SQL | Snowflake | Spark | Statistical modeling | Time Series | Uplift Modeling | Web Services