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

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

Machine Learning, React, FastAPI, Python, Sql, Cloud Platforms, Data Visualization BI Tools, LangChain or Agentic Frameworks, Generative AI LLMs, Git CI-CD

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

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

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

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

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