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Chinmaya Venkataraman

Technology Consultant

Chinmaya is a results-oriented Technology Consultant with two years of experience in data science, AI/ML, and mathematics. He specializes in data analysis, predictive modeling, and generative AI to address complex business challenges. With expertise in Agile methodologies, custom solution development, and system integrations, Chinmaya excels at delivering innovative, data-driven solutions that drive strategic decision-making.

Work Experience

Consultant at Ernst & Young LLP

Oct '24 - Present

  • Generative AI Solution: Developed a generative AI solution to analyze market sentiment towards the client by aggregating data from multiple sources, performing sentiment analysis, and creating an NPS score dashboard to visualize the results. This enabled the client to make timely interventions and maintain a positive NPS score.
  • Stakeholder & Resource Management: Managed stakeholder communications, risk management, and resource planning for a banking client in the Asia-Pacific region. Supported financial modeling and revenue forecasting, delivering regular reports that informed senior leadership decisions.
  • Technology Adoption & AI/ML Integration: Collaborated with a telecommunications client to assess technology adoption and organizational maturity. Used data-driven surveys to generate insights that helped incorporate AI/ML methods, improving business outcomes.
  • ETL Process Leadership: Led ETL processes, including data cleaning, transformation, and modeling, to ensure data integrity. Applied data augmentation techniques to improve model performance and generate actionable insights that optimized business processes.

Associate Consultant at Ernst & Young LLP

May '23 - Sept '24

  • Business Development & Client Engagement: Assisted in the preparation of proposals and RFP responses, developing impactful presentations and decks that communicated value propositions, supporting client engagement and fostering new business opportunities.
  • Process Documentation & Improvement: Contributed to process documentation and mapping for an agri-tech subsidiary, identifying dependencies and areas for improvement. Supported change management initiatives to enhance operational efficiency.
  • Business Analysis & AI/ML Application: Performed business analysis for clients in manufacturing, power generation, and pharmaceuticals, using data insights and AI/ML techniques to improve processes and increase yields by 15%.

Projects

Capstone project - 'VisionRay - Prediction of Covid-19 Pneumonia'

Trained Efficient-net deep learning model to detect COVID-Pneumonia from chest X-rays. Used object detection to localize affected areas of patient lung. Won 'Best Capstone Project'.

Tech used: Pytorch, OpenCV, scikit-learn, streamlit

Big Data with MongoDB and PySpark

Uploaded data to hosted MongoDB server and imported data remotely to perform EDA using Spark Dataframes. Built Machine Learning pipelines and implementing the following models: Decision Tree, Random Forest, GBM, XgBoost, SVM, Naive Bayes

Tech used: PySpark, PyMongo

Machine Learning with Hyperopt on Emissions Data

Cleaned emissions data, applied regression and various machine learning techniques, performed hyperparameter tuning to get best results. Performed residue analysis and hypothesis testing to ensure validity of findings.

Tech used: Scikit-learn

Web scraping with scrapy

Scraped google news for daily news updates on a topic, decoded redirect links, trained machine learning model to extract article, stored it in a database and performed sentiment analysis on resulting data.

Tech used: Scrapy, Ollama