Data Science professional with nearly 4 years of experience in analytics and applied machine learning, with growing focus on Generative AI and intelligent automation. Strong interest in Generative AI and intelligent auto…
Data Science professional with nearly 4 years of experience in analytics and applied machine learning, with growing focus on Generative AI and intelligent automation. Strong interest in Generative AI and intelligent automation, with hands-on experience in building ML models and RAG-based systems using LLMs and vector databases. Curious about emerging AI tools and focused on building practical proof-of-concept solutions that can create real business impact. Comfortable working across teams and explaining technical ideas in a structured and simple manner.
Worked with large-scale structured datasets to perform advanced data preprocessing, transformation, and validation for analytics and modeling use cases.
Explored opportunities for process automation using Python-based workflows.
Supported data-driven decision-making by presenting structured analytical findings to stakeholders.
Utilized SQL and Python to extract, manipulate, and analyze high-volume datasets for business insights.
Conducted exploratory data analysis (EDA) to identify trends, patterns, and anomalies influencing business decisions.
Applied statistical techniques including hypothesis testing and distribution analysis to validate data assumptions.
Engineered feature-ready datasets and data transformation workflows to support predictive modeling and advanced analytics initiatives.
Automated recurring analytical workflows using Python, improving operational efficiency.
Collaborated with cross-functional teams to translate business requirements into data-driven insights.
Worked with large-scale structured datasets to perform advanced data preprocessing, transformation, and validation for analytics and modeling use cases., Explored opportunities for process automation using Python-based workflows., Supported data-driven decision-making by presenting structured analytical findings to stakeholders., Utilized SQL and Python to extract, manipulate, and analyze high-volume datasets for business insights., Conducted exploratory data analysis (EDA) to identify trends, patterns, and anomalies influencing business decisions., Applied statistical techniques including hypothesis testing and distribution analysis to validate data assumptions., Engineered feature-ready datasets and data transformation workflows to support predictive modeling and advanced analytics initiatives., Automated recurring analytical workflows using Python, improving operational efficiency., Collaborated with cross-functional teams to translate business requirements into data-driven insights.
Built end-to-end machine learning solutions from data preprocessing to model evaluation and inference pipeline development.
Compared different ML/NLP models to understand performance differences across use cases.
Designed and implemented ML models including Logistic Regression, Random Forest, K-Means, and Time Series forecasting.
Developed deep learning models using TensorFlow/Keras including LSTM-based sentiment analysis systems.
Built Retrieval-Augmented Generation (RAG) pipelines using LangChain, Hugging Face Transformers, Sentence-BERT, and ChromaDB.
Implemented similarity search using vector embeddings for context-aware conversational AI systems.
Evaluated models using performance metrics such as Accuracy, Precision, Recall, F1-score, and ROC-AUC.
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