Senior Data Scientist

Tasks

• Apply statistical predictive and prescriptive modeling
• Build and maintain production grade data science solutions
• Build forecasting models
• Build intelligent agents and AI decision systems
• Collaborate with engineering and analytics teams on data readiness
• Design and implement causal inference methods
• Develop and deploy machine learning models
• Develop optimization approaches for resource allocation and scheduling
• Embed causal reasoning into decision systems
• Ensure model explainability and business actionability
• Implement model monitoring and lifecycle management
• Integrate generative AI into data science workflows
• Integrate models into scalable APIs and platforms
• Review and validate modeling approaches across teams

Perks/Benefits

• Growth opportunities
• Inclusive culture
• International career opportunities
• Values-driven culture

Skills/Tech-stack

API Integration | Agentic Systems | Agile | Apache Airflow | Apache Spark | Attribution | Azure AI | Azure Machine Learning | Causal Inference | DBT | Data Pipelines | Databricks | Databricks SQL | Decision Intelligence | Experiment design | Experimental Methods | Forecasting | Generative AI | Geo-experiments | Google BigQuery | Language Models | Large Language Models | Machine Learning | Marketing Analytics | Marketing Mix | Marketing Mix Modeling | Marketing attribution | Microsoft Fabric | Mix Modeling | Model Deployment | Model Monitoring | Optimization | Probabilistic Forecasting | Python | Quasi Experimental | Quasi-experimental methods | RAG | SQL | Series analysis | Snowflake | Statistical modeling | Synthetic control | Time Series | Time Series Analysis | Uplift Modeling