
Data Driven Decision Maker
2 days ago
- Data Analysis & Visualization
- Perform detailed data analysis using various libraries such as pandas, numpy, and plotly to identify trends, detect outliers, and address missing values.
- Develop automated EDA reports to support data-driven decision-making.
Feature Engineering & Selection
Key Responsibilities:- Develop robust feature engineering techniques such as encoding (one-hot, label, ordinal), TF-IDF, and domain-specific transformations.
- Engineer features from time-series datasets using lags, rolling statistics, and seasonal patterns.
Model Support & Optimization
Key Responsibilities:- Collaborate with ML engineers to transform features into model-ready datasets.
- Contribute to model pipeline enhancements by integrating engineered features and tracking their impact using A/B testing or evaluation metrics.
Requirements:
Education:- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
- Strong programming skills in Python with experience in data science libraries such as pandas, numpy, scikit-learn, and plotly.
- Deep expertise in data visualization, statistical analysis, and report generation using seaborn, matplotlib, sweetviz, and pandas-profiling.
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