Data Scientist | Analyst | MLOps Engineer
I am a passionate and results-oriented data professional with expertise in data science, analytics, and MLOps. I thrive on transforming complex data into actionable insights and building robust, scalable machine learning pipelines. My experience includes data analysis, statistical modeling, and deploying machine learning models into production environments. I am always eager to learn new technologies and take on challenging projects.
Python, R, SQL, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, PyTorch, Matplotlib, Seaborn, Plotly, Tableau
Docker, Kubernetes, Jenkins, Airflow, MLflow, AWS, GCP, Azure
Apache Spark, Hadoop, Kafka, Hive
Analyzed IPL data using Apache Spark and Databricks, with data stored on Amazon S3. Created visualizations using matplotlib and seaborn to uncover insights.
A real-time data streaming pipeline using Apache Airflow, Kafka, Spark, Docker, and Cassandra.
A comprehensive platform to analyze electronic Medication Administration Records (eMAR) in real-time, identify potential risks, and provide actionable insights to healthcare providers.