I am a Data & Analytics Professional with hands on experience working on cloud based data and analytics platforms,
CI/CD automation, and system integrations across enterprise environments. My work focuses on analytics enablement,
data integration configuration, operational monitoring, and system reliability, including zero copy data integration,
secure data ingestion processes, interactive dashboards, and structured production releases.
With a strong engineering mindset shaped by CI/CD automation and cross functional collaboration, I primarily work
with SQL, Python, and data integration workflows. I am currently pursuing a Master's in Machine Learning and
Mathematical Modelling, strengthening my foundation in applied machine learning through academic and personal
projects, and seeking hands on engineering roles where I can contribute to scalable, production oriented systems.
Sept 2018 - Oct 2018
Sep 2025 - Present
2014 - 2018 (May)
Issued: Dec 2025
Demonstrated skills in designing, building, and deploying scalable AI solutions using Azure AI services, including cognitive services, machine learning, and responsible AI practices.
Issued: Dec 2023
Demonstrated skills in Azure Machine Learning, data science, and analytics for designing, training, evaluating, and deploying machine learning models at scale.
Issued: Oct 2024
Built a strong foundation in AI for CRM, including language models, ethical AI principles, data insights, and intelligent automation within Salesforce solutions.
Issued: Nov 2024
Demonstrated expertise in Salesforce Data Cloud implementation, data integration, unification, and analytics to deliver scalable, data driven business solutions.
A machine learning project focused on predicting vehicle insurance policy lapses, from data preprocessing to model evaluation.
This project focuses on building a machine learning based classification system to predict whether a vehicle insurance policy is likely to lapse, using customer and policy related data.
The work covers the core machine learning pipeline including data ingestion, feature engineering, model training, evaluation, and a Flask-based prediction interface.
Technologies
Python, Pandas, NumPy, Scikit-learn, Flask
Focus Areas
Data preprocessing, feature engineering, classification modeling, model evaluation, and prediction API development
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