1. Data Science & Modelling :
- Independently complete end-to-end data science projects including data collection, analysis, and Modelling.
- Conduct exploratory data analysis to uncover trends and patterns.
- Develop, evaluate, and refine machine learning models to improve predictive accuracy.
- Experience working with LLMs and using traditional NLP techniques.
2. Insight Generation & Communication :
- Extract actionable insights from complex datasets and communicate findings effectively.
- Present results using clear visualizations and storytelling techniques.
- Support decision-making through data-backed recommendations.
3. Collaboration & Integration :
- Work closely with data engineering teams to ensure seamless data pipeline integration.
- Collaborate with cross-functional stakeholders to understand business needs and translate them into analytical solutions.
- Assist in documentation and knowledge sharing across teams.
4. Tools & Technology :
- Utilize Python and data science libraries (e.g., pandas, scikit-learn, matplotlib) for analysis and Modelling.
- Work within Databricks or similar cloud-based environments.
- Use SQL for data extraction and transformation.
- Apply data visualization tools and packages to create intuitive dashboards and reports.
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