Data Scientist Mid-Level
Tasks
- Apply LLM enabled workflows for business analysis
- Build recommendation and decision support models
- Collaborate with data and analytics teams on solutions
- Conduct experimentation analysis and evaluation
- Design and execute forecasting and segmentation analyses
- Develop machine learning models
- Document methodology features and model decisions
- Follow governance privacy and responsible AI standards
- Improve reproducibility documentation and scalability of workflows
- Perform anomaly detection and propensity modeling
- Train tune validate and evaluate models
- Translate business questions into analytical approaches
Perks/Benefits
- Autonomy
- Diversity
- Growth opportunities
- International careers
- Team knowledge sharing
- Values-driven culture
Skills/Tech-stack
Agile | Apache Spark | Azure DevOps | Azure Machine Learning | Cloud platform | Databricks | Deep learning | Embeddings | Git | GitHub | Google Cloud | Google Cloud Platform | Jupyter Notebooks | LightGBM | Looker | MLflow | Machine Learning | Matplotlib | Microsoft Azure | NumPy | OpenAI API | Pandas | Plotly | Power BI | Prompt engineering | PySpark | Python | SQL | SciPy | Scikit-learn | Seaborn | StatsModels | Tableau | Vertex AI | XGBoost
Education
N/A
Roles
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