Machine Learning, Version Control, Unit Testing, XGBoost, Python, software engineering best practices, scikit-learn, reinforcement learning, causal inference techniques, Packaging, contextual multi-armed bandits, quasi-experimental methods, uplift modeling, modular code, counterfactual analysis

Tensorflow, Pytorch, Docker, Aws Ec2, Python, Computer Vision, ML DL frameworks, Time-Series Modeling, Tabular ML

S3, Aws Services, Sql, Tensorflow, Lambda, Pytorch, Data Visualization, Python, Step Functions, Scikit-learn, R, ETL workflows

data engineering , Elk, Prometheus, Kafka, Grafana, Datadog, Tensorflow, Pytorch, Terraform, Docker, Python, Azure DevOps, AWS, Hadoop, Google Cloud Platform, Cloudformation, Apache Spark, Jenkins, MLops, Software Engineering, Spark, Databricks, Azure, Kubernetes, Airflow, MLflow, Flink, GitHub Actions, Bicep, Machine Learning Engineering, Scikit-learn, Azure Monitor

Tableau, Tensorflow, Data Science, Pytorch, XGBoost, Python, AWS, Hadoop, Power Bi, Sql, Hive, MLops, Spark, Azure, scikit-learn, Cloud Platforms, Dash, Model Deployment, Generative AI, Plotly, Unstructured Data Analysis, Statsmodels, Agentic AI, Model Monitoring, Retrieval Augmented Generation

Sql, Java, Adf, Hadoop, Tableau, Power Bi, Python, Azure, Scala, Spark, Data bricks, machine learning frameworks, optimization solvers

Machine Learning, Statistical Analysis, Tensorflow, Deep Learning, Pandas, Numpy, Pytorch, Python, Generative AI, Agentic AI systems, scikit-learn, Vision capability streams, R, MLOps practices, Fine-tuning pre-trained models