Abhijith ML Engineer
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๐Ÿš€ Curious About Data Science? Let's Explore It Together!
Ever wondered how YouTube recommends videos or how self-driving cars work? I help students dive into the world of Data Science through engaging, hands-on sessions designed for absolute beginners to budding tech enthusiasts.

๐Ÿ‘จ‍๐Ÿซ What I Teach

Python programming (through fun, project-based learning)

Data wrangling & storytelling using pandas and matplotlib

Beginner-friendly machine learning with real use cases

Building mini-projects like recommendation systems & chatbots

STEM thinking: problem-solving, experimentation, and creativity

๐ŸŽฏ Who I Teach
I work with curious minds—middle schoolers, high schoolers, and college students. Whether you are prepping for a science fair, a coding competition, or just love tech, I will tailor each session to your pace and goals.

๐ŸŽ“ Why Learn With Me?
With over 10 years of experience in AI and ML, I bring real-world insights and a fun approach to learning. My teaching emphasizes clarity, confidence, and practical skill-building.

๐Ÿ“… Ready to Begin?
Book a trial session and let's make your data science journey fun, empowering, and impactful!

Subjects

  • Predictive Modelling Beginner-Expert

  • Natural Language Processing Beginner-Expert

  • Data cleaning, visualization, validation, mining, and analysis Beginner-Expert

  • Data Analysis with Python Beginner-Expert

  • Large Language Models LLMs Beginner-Expert

Experience

  • Machine Learning Engineer (Jun, 2023–Present) at Health Insurance Company
    • Built and deployed an end-to-end ML pipeline for claims processing, fraud detection, and risk prediction using Databricks (PySpark, MLflow), AWS EMR, and SageMaker, reducing processing time by 20%.
    • Developed AI-driven approval models (XGBoost, CAT Boost, LightGBM) that automated low-risk approvals and routed high-risk claims for manual review, increasing approval efficiency by 10%.
    • Enhanced fraud detection with transfer learning, fine-tuning BERT (Large Language Model) on insurance documents, improving anomaly detection accuracy by 25% and preventing fraudulent claims before payout.
    • Integrated GenAI-powered solutions, leveraging Amazon Kendra & Bedrock to enable context aware document retrieval and LLM-based claim explanations, enhancing auditability & reducing investigation time.
    • Developed an LLM-powered chatbot for claimants to retrieve policy details, check claim statuses, and initiate fraud disputes, reducing customer service response time by 30% while ensuring compliance with AWS cloud security.
  • Software Engineer | Data Scientist (Mar, 2010–Jan, 2020) at Banking & Financial Industry
    • Developed & deployed an AI-powered chatbot for Premier clients, leveraging TensorFlow, NLTK, and early NLP models for intent recognition & query routing, reducing response times by 30%, improving customer satisfaction by 25%, and decreasing call center volume by 20% through
    automation.
    • Built & optimized fraud detection models (Decision Trees, Logistic Regression, SVM) to enhance risk assessment, achieving a 15% improvement in fraud detection accuracy while minimizing false positives, ensuring compliance with financial risk regulations.
    • Developed ML models for credit risk assessment & financial product recommendations using Scikit-learn (K-Means, Random Forest, Logistic Regression), increasing client engagement by 20% and improving loan approval efficiency by 10%.
    • Implemented NLP-driven document classification & sentiment analysis using NLTK and spaCy, automating data extraction from unstructured financial reports, reducing manual workload by 40%, and improving processing accuracy.

Education

  • Master of Science in Computer Engineering Science (Aug, 2021–Dec, 2023) from California Sate University–scored 3.7 | 4.0

Fee details

    US$10–30/hour (US$10–30/hour)

    I provide personalized teaching and mentoring in Data Science, tailored to the student's level and pace. My sessions include hands-on guidance in Python, statistics, data analysis, machine learning, and real-world projects. The fee varies depending on the topic complexity, student experience, and session length. For beginners and school students, I offer discounted rates starting at $10/hr. Advanced topics, one-on-one mentorship, and project guidance may go up to $30/hr. My goal is to make learning Data Science accessible, practical, and engaging.

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