Customer-focused Solutions Engineer with a track record of delivering scalable, high-performance cloud based data solutions that drive business impact. Committed to operational excellence, risk discipline, and innovation, ensuring integrity, efficiency, and long-term value in every solution.
🔭 I'm Currently Working On:
- Exploring advanced machine learning techniques for predictive modeling.
- Enhancing my skills in cloud computing with AWS, Azure, and GCP.
- Developing interactive data visualizations using Power BI and Tableau.
🌱 I'm Currently Learning:
- Quantitative Research - Virtual Simulated Internship
- Google Cloud for Data Analytics
💼 Experience:
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Data Engineer, Amazon, India | Mar 2023 - Aug 2023 (Contracted: Technical Lead, DISYS, India) Understanding the business needs, identifying gaps, architecting solutions based on AWS and open source techs, development, deployment and monitoring support.
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Consultant, Capgemini India Pvt Ltd, India | Jun 2021 - Feb 2023 Collaboration with Clients for business requirements, technical solutions design and planning for replatforming ETL pipelines from IBM Informix to GCP, team management and track project progress, development, and deployment.
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Lead Machine Learning Engineer, Omdena | April 2021 - May2021 (Internship) Developed image-denoising models to enhance satellite image clarity, improving feature extraction. Built CNN-based classification models, categorizing rooftops into four types for solar panel suitability assessment.
🎓 Education:
- MSc Business Analytics, University of Surrey, UK | September 2024 | Grade: 71.5
- MSc Data Science and Analytics, University of London, UK | September 2019 | Grade: 66.62
- BTech Information Technology, Kalasalingam University, India | May 2011 | Grade: 77.7
🚀 Skills:
- Programming: Python, PySpark, R, Java, SQL (PL/SQL, NoSQL)
- Cloud: AWS (S3, Glue, Lambda, Redshift, API Gateway), GCP (BigQuery, IAM, Dataproc)
- Data Engineering & DevOps: Data Modeling, ETL, Spark, Airflow, Control-M, GitHub, Jenkins
- ML Analytics: ML, AI, NLP, Power BI, Quicksight, STATA, SAS Viya, IBM SPSS, @RISK
- Project Management: Agile(Scrum), JIRA, Confluence, CI/CD, SDLC
🔧 Projects:
Air Quality and Impacting Factors (NASA Space Apps Challenge 2024): A research-based geospatial dashboard to analyze PM2.5 pollution in India, integrating Sentinel data and machine learning models for air quality forecasting.
Predictive power of Social Media data: Sentiment Analysis on twitter data leveraging big data analytics using PySpark with lexicon-based and deep learning models.
Retail Demand forecasting: A predictive revenue optimization framework for London’s bike-sharing system, leveraging big data analytics using pyspark and demand forecasting & pricing strategies.
Insurance marketing: A customer segmentation model for insurance marketing, using predictive analytics to classify customer profiles, optimizing targeted outreach and improving ROI.
Google app store revenue analysis: A statistical analytics on Google App store revenue, evaluating the impact of pricing, monetization strategies, and app ratings.
International Bank Marketing Campaign: A marketing campaign analysis leveraging insights for an international bank to promote their fixed term saving account scheme using IBM SPSS Statistics.
Customer Churn Analysis: Customer churn analysis using ML and python enhancing retention strategies.
Let's connect and collaborate on exciting data science projects! Feel free to reach out for discussions on data-driven solutions, machine learning applications, or anything tech-related.