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Vinay M H

A results-driven Data Scientist and AI-ML Engineer aiming to leverage extensive experience in predictive modeling, machine learning solutions, and AI technologies to drive innovation, operational efficiency, and elevate user engagement in a forward-thinking.

  • Role

    Data & Pytorch Engineer

  • Years of Experience

    1.83 years

Skillsets

  • pandas
  • Git - 2 Years
  • MySQL - 1 Years
  • Scikit-learn
  • Seaborn
  • DBMS
  • Matplotlib
  • REST API
  • Debugging
  • Postgre SQL
  • NumPy
  • TensorFlow
  • PyTorch
  • Django
  • Git
  • SQL - 2 Years
  • Python - 3 Years

Professional Summary

1.83Years
  • Apr, 2025 - Present1 yr

    Lead Associate (AI)

    I-PAC (Indian Political Action Committee)
  • Jan, 2025 - Apr, 2025 3 months

    AI Data Scientist

    VerifiedTalent
  • Sep, 2023 - Mar, 2024 6 months

    Data Engineer

    Aiml Data Analytics Solutions Pvt Ltd (Open Data Fabric)
  • Feb, 2022 - Mar, 2022 1 month

    Machine Learning Intern

    SkillVertex

Applications & Tools Known

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    AWS (Amazon Web Services)

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    Google Cloud Platform

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    Azure Machine Learning Studio

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    VS Code

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    PyCharm

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    Postman

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    PostgreSQL

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    Google Cloud SQL

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    Git

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    REST API

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    Python

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    Jira

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    VS Code

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    Confluence

Work History

1.83Years

Lead Associate (AI)

I-PAC (Indian Political Action Committee)
Apr, 2025 - Present1 yr

    Voice Agents

    Agentic-AI

    Large Language Models (LLM)

AI Data Scientist

VerifiedTalent
Jan, 2025 - Apr, 2025 3 months

    Architected and launched an AI-powered job recruitment & talent profile creation assistant, integrating OpenAIs GPT models to enhance recruiter-talent interactions, automating job recommendations, and improving hiring efficiency.

    Built an AI-driven profile enrichment system leveraging LLMs and Named Entity Recognition (NER) to extract and validate key candidate attributes, ensuring 100% structured and high-quality data ingestion.

    Refined AI assistant workflows by reducing OpenAI API latency by 40%, using caching mechanisms and optimized prompt engineering for faster query resolutions.

    Embedded LLM-powered auto-correction and validation in recruiter and talent profile workflows, achieving 100% data consistency through structured JSON generation and multi-stage validation.

    Developed an LLM-driven resume parsing and ranking system, leveraging SBERT-based semantic similarity and fuzzy matching, improving candidate scoring accuracy for recruiters.

    Optimized prompt engineering strategies, designing task-specific prompts that improved AI-generated response accuracy and coherence in talent evaluation.

Data Engineer

Aiml Data Analytics Solutions Pvt Ltd (Open Data Fabric)
Sep, 2023 - Mar, 2024 6 months
    Spearheaded the integration and deployment of LLM(Llama2), conversational AI model, onto server infrastructure using AWS Sagemaker and Lambda, resulting in a 25% improvement in customer interaction efficiency and enhancing user experience. Designed, developed, and deployed robust back-end systems and APIs using Python, Django, and GCP services such as App Engine and Cloud SQL, greatly improving system performance and reliability. Integrated comprehensive loan APIs and 4+ secure payment gateways by hitting gateway APIs within RESTful services to facilitate seamless, efficient, and secure collection of loan amounts, increasing overall financial operations efficiency. Orchestrated Git for version control and implemented CI/CD pipelines using GitHub actions with on-push deployment methods, leading to fewer deployment errors and faster deployment speeds. Pioneered a new underwriting method by analyzing detailed financial statements and transactional data to assess risk and profitability, optimizing the financial decision-making.

Machine Learning Intern

SkillVertex
Feb, 2022 - Mar, 2022 1 month
    Engineered a predictive model to determine employee promotion eligibility using advanced machine learning techniques, achieving an accuracy of 93.57% through rigorous testing, validation and iterative improvements over multiple training cycles. Performed extensive Exploratory Data Analysis (EDA) and feature engineering to effectively handle missing values, optimize a dataset comprising 15 distinct features, and enhance classification accuracy through techniques such as normalization. Created comprehensive data-visualizations and analytical insights by leveraging powerful Python libraries such as NumPy, Pandas, Seaborn, and Scikit-Learn, significantly enhancing data comprehension and improving decision-making accuracy.

Achievements

  • Engaged in Accenture North Americas Data Analytics and Visualization virtual experience program, accomplished the tasks by understanding the given project, and performed the data cleaning, modeling & then presented the insights to the client.
  • Tailored the reward function using the cutting-edge PPO Reinforcement Learning Algorithm and assessed in AWS Deepracer student league competition by finishing the 3 laps and pre-qualified for the prestigious AI&ML Scholarship.

Major Projects

1Projects

Machine Learning Optimization in Steel Making

Jun, 2022 - Jan, 2023 7 months
    Leveraged machine learning and statistical algorithms to enhance efficiency in the industrial steel production, contributing to improved production quality, reduced waste and optimizing operational workflows through detailed analysis. Optimized manufacturing operation parameters by employing predictive monitoring techniques, achieving an R2 score of 0.685, thereby increasing system reliability, consistency, and overall operational efficiency through continuous parameter adjustments. Implemented a variety of machine learning models, including Linear Regression, Random Forest Regressor, SVM, OLS Regression, XGBoost, and ANN, to accurately predict optimal parameters and maximize yield.

Education

  • Dual Degree in Metallurgy & Materials Engineering [B.Tech + M.Tech]

    Indian Institute of Technology Madras - IITM (2023)

Certifications

  • Microsoft azure ai-900: certified in machine learning workloads, text analytics with a score of 816/1000

  • Machine learning: concluded machine learning course given by stanford university offered through coursera

  • Aws machine learning foundations: certified in the aws-ml program offered by aws & udacity.

  • Python dsa [nptel]: examined in programming, data structures & algorithms using python from nptel

Interests

  • Cricket
  • Badminton