data engineering , Machine Learning, Data Modeling, Sql, Tensorflow, Pytorch, Gcp, MLops, XGBoost, Spark, Databricks, Predictive Analytics, Azure, Python, AWS, Generative AI, data pipelines, Scikit-learn, Optimization, AI-driven decision systems, Statistical Modeling

Tensorflow, Machine Learning, Pytorch, Pyspark, Sklearn, Python, Time Series Forecasting

Code Review, Azure, Python, Production ML and model deployment, AI-assisted coding workflows and coding agents such as Codex, Technical mentorship and communication, Forecasting, Generative AI, Reusable package design, Optimization, Applied statistics modeling and rigorous evaluation, Production-quality code testing, Open-source contribution and reusable package development, experimentation, Data pipelines, Databricks environments

Sql, Deep Learning, Machine Learning, Predictive Modeling, Python, Site experimentation, Statistical methods, Ensemble models, R, Inferential analysis, experimentation, Transformer-based methods

causal inference , Python, Sql, product analytics, experimentation design, generative AI tooling, Ai, event instrumentation

Data Lineage, Machine Learning, Datadog, Agile, Scrum, Generative AI, Compliance, LLM Evaluation Methods, Model APIs, Auditability, Arize, Subject Matter Expert Annotation Workflows, Deterministic Evaluations, Online Evaluations, Responsible AI Practices, Bias Evaluation, Kubeflow, Prompt Engineering

snowflake , probability , triton , Pytorch, Docker, Postgres, Python, BigQuery, Sql, MLops, Spark, Statistical Inference, Airflow, prompt tuning, A-B design, pgvector, Hugging Face, Ray, MLflow, class weighting, Evaluation, RLHF, PEFT, fine-tuning, experiment tracking, transfer learning, vLLM, resampling, SageMaker, Bayesian Methods, dbt

Matplotlib, Hadoop, Power Bi, data mining, Tableau, Google Cloud, Spark, Azure, Python, AWS, Machine Learning Algorithms, data visualization tools, MLOps practices, R, Statistical Modeling, feature engineering