Data Scientist Mid-Level
Tasks
- Build and maintain notebook based reproducible workflows
- Collaborate with data analysts and data engineers to align solutions
- Conduct experimentation analysis and recommendation oriented analysis
- Design and execute segmentation forecasting propensity and anomaly detection analyses
- Develop analytical statistical machine learning and applied AI solutions
- Document assumptions methodology feature logic and model decisions
- Follow governance privacy and responsible data and AI standards
- Improve reproducibility evaluation and scalable analytical workflows
- Support LLM enabled and AI assisted analysis workflows
- Train tune validate and evaluate machine learning models
- Translate business questions into analytical approaches and models
Perks/Benefits
- Collaborative work culture
- Growth opportunities
- International careers
- Meaningful impact
- Values-driven culture
Skills/Tech-stack
AI Services | Agile | Apache Spark | Azure AI | Azure AI Services | Azure DevOps | Azure Machine Learning | BigQuery | Cloud platform | Databricks | Embeddings | Experimentation | Feature Engineering | Git | GitHub | Google Cloud | Google Cloud Platform | Jupyter Notebooks | LightGBM | Looker | MLflow | Machine Learning | Matplotlib | Microsoft Azure | Model Evaluation | NumPy | OpenAI Compatible | OpenAI Compatible APIs | Pandas | Plotly | Power BI | Probability | Prompt engineering | PySpark | Python | SQL | SciPy | Scikit-learn | Seaborn | Snowflake | Statistics | StatsModels | Tableau | Vertex AI | XGBoost
Education
N/A
Roles
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