Scripting languages (e.g. Python), Data querying languages (e.g. SQL), Power analysis and minimum detectable effect (MDE) calculations, Machine Learning, Data mining, Statistical Modeling, Applied statistics, Large-scale analytics

Data Manipulation, Data Transformation, Python Programming, data pipeline development, logic-based workflows, Analytics, SQL proficiency, Dataiku, common coding tools within Dataiku, Excel-like analytical methods

prophet , Machine Learning, Tensorflow, Pytorch, XGBoost, Python, Sql, Deep Learning, Git, Kubernetes, scikit-learn, Temporal Convolutional Networks, Random Forests, GRU, Integrated Gradients, Gradient Boosting, data visualization tools, Time Series Models, LSTM, SHAP, LightGBM, Statistical models, counterfactuals, statsmodels, permutation importance, transformer-based models

causal inference , Machine Learning, Hadoop, Sql, Hive, MLops, Spark, Python, Generative AI, Optimization, Statistical Measurement, Operations Research, AI Engineering, Simulation

snowflake , Tensorflow, Pytorch, Gcp, MLops, XGBoost, Azure, Python, Sql, AWS, Scikit-learn

Python, Machine Learning, R, ML algorithms, data science pipeline, data-structures

Numpy, Pandas, Python, Sql, Statistical Analysis, scikit-learn, causality, impact evaluation, Measurement

data wrangling , data engineering , Github, Pyspark, API design, Sql, Integration, Databricks, Python, Azure DevOps, Forecasting, MLflow, anomaly detection, time series modeling, feature pipeline design, dataset preparation, data quality troubleshooting