Data Scientist – Machine Learning & GenAI
Tasks
- Build dashboards and reporting assets
- Collaborate with business stakeholders on data requirements and metrics
- Design and build segmentation and predictive models
- Develop NL to SQL solutions
- Develop RAG systems
- Develop and evaluate modular GenAI features
- Document data sources and support continuous improvement
- Draft presentation materials for stakeholders
- Implement analytics enabled solutions
- Leverage LLMs to create features from unstructured data
- Own feature engineering pipeline for ML and AI models
- Prepare clean analyze datasets for ML and AI features
- Track tasks in JIRA
- Translate analytical findings into business recommendations
Perks/Benefits
Skills/Tech-stack
Azure | Clustering | Context engineering | Data Analysis | Data Modeling | Databricks | Decision Trees | Exploratory Data Analysis | Feature Engineering | Git | GitHub | LLM | MLOps | Machine Learning | Model Training | Model Validation | NL-to-SQL | NumPy | PCA | Pandas | Power BI | Prompt engineering | PySpark | Python | RAG | Regression | SQL | Scikit-learn | Survival analysis | Tableau
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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