"Building intelligent systems that don't just predict the future—they optimize it."

I'm a Senior ML & AI Engineer with 5+ years of experience building production-grade AI solutions across LLMs, optimization, and predictive analytics. Currently leading data science initiatives at Axtria – Ingenious Insights while pursuing 3 advanced AI/ML programs simultaneously (UT Austin, IIIT Bangalore, Deakin University).

What I Do:

• 🧠 Build and deploy GenAI applications using LLMs, RAG systems, and Azure OpenAI
• 🎯 Architect marketing mix optimization platforms serving Fortune 500 pharma clients (Bayer, Merck, Novartis, Janssen)
• 🚀 Design scalable MLOps pipelines with Docker, MLflow, FastAPI, and CI/CD automation
• 📊 Lead cross-functional teams delivering 25+ data science projects with measurable business impact
• 🎓 Mentor engineers and train 70+ professionals in ML, Python, SQL, and optimization strategies
• 🏗️ Own 10+ product capabilities from design to deployment with enterprise-scale impact

Career Highlights:

• 🏆 4 promotions in 3.5 years: Analyst → Associate → Senior Associate → Project Leader
• ⚡ 98-100% error-free delivery rate across production releases
• 🎯 95%+ on-time delivery for 10+ major product capabilities
• 💡 Led GenAI integration using Azure OpenAI improving user engagement by 40%
• 🚀 Reduced execution time by 72% and memory consumption by 63%
• 📈 Increased HCP adoption rates by 38% and model accuracy by 35%

Specializations: Machine Learning • Deep Learning • Predictive Analytics • Statistical Modeling • Feature Engineering • Time Series Forecasting • Computer Vision • NLP

Expertise: RAG Systems • Prompt Engineering • LLM Fine-Tuning • Embeddings • Semantic Search • Inference Optimization • LlamaIndex

Vector Databases: FAISS • Pinecone • Weaviate

Tech Stack: Python • Optimization Algorithms • Azure • MLOps • SaaS

• Led development of enterprise-scale Marketing Mix Modeling framework for Fortune 500 pharma clients
• Architected 10+ optimization capabilities including Portfolio Optimization, Multi-Level Constraints, and Monthly Gating
• Implemented advanced algorithms (COBYLA, SLSQP, etc.) with non-linear response modeling
• Delivered 25+ MMM projects for Bayer, Merck, Novartis, Janssen with measurable ROI improvements
• Built Pre/Post-Optimization APIs reducing execution time by 72% and memory by 63%

Tech Stack: XGBoost • MLflow • Docker • GitHub Actions • Streamlit • Hugging Face

• Built end-to-end MLOps pipeline with automated CI/CD for customer purchase behavior prediction
• Engineered feature pipelines handling missing values, encoding, and stratified splits
• Implemented XGBoost classification with hyperparameter tuning and MLflow tracking
• Containerized with Docker and deployed real-time Streamlit app to Hugging Face Spaces
• Demonstrated modern model governance with datasets and artifacts stored on HF Hub

Tech Stack: Random Forest • Gradient Boosting • Time Series • IoT Data Processing

• Built predictive maintenance system forecasting engine failures using time-series sensor data
• Performed comprehensive feature engineering with lag features capturing degradation patterns
• Trained multiple models with cross-validation optimized for imbalanced failure prediction
• Developed automated evaluation pipeline tracking precision, recall, F1-score, and ROC-AUC
• Created interactive dashboards for engineering decision support and maintenance scheduling

Career Progression (4 promotions in 3.5 years):

Project Leader – Data Science / ML (May 2024 – Present)

• Leading 10+ major product capabilities with 95%+ on-time delivery and 98-100% error-free releases
• Architecting scalable optimization systems serving enterprise pharmaceutical clients
• Mentoring team of 5+ data scientists and training 70+ employees

Senior Associate – Data Scientist (May 2023 – Apr 2024)

• Owned MMX optimization enhancements and algorithm implementations (COBYLA, SLSQP, CCSA)
• Led high-impact POCs including Grid Selection, LSTM forecasting, and execution time optimization
• Supported multiple global projects for Novartis brands across Poland and Germany

Associate – Data Scientist (May 2022 – Apr 2023)

• Delivered client-specific enhancements for Janssen and Novartis with custom segmentation
• Designed performance-optimized workflows improving memory utilization significantly
• Researched and validated SLSQP algorithm implementation for Optimization API

Analyst – Data Scientist (Jul 2021 – Apr 2022)

• Built Early Adopter Predictor increasing HCP targeting adoption by 38%
• Delivered 5 Marketing Mix Modeling projects for top US pharma clients
• Established foundation in MMM techniques and analytics workflow delivery

• 🎓 Deakin University, Australia | Masters of Data Science (Jun 2026 – Jun 2027)

• 🎓 International Institute of Information Technology, Bangalore | Executive PGP in Applied AI & Agentic AI (Dec 2025 – Aug 2026)

• 🎓 The University of Texas at Austin, USA | Post Graduate Program in Artificial Intelligence & Machine Learning (Feb 2025 – Mar 2026)

• 🎓 Birla Institute of Technology and Science, Pilani | B.E. & M.Sc. (Integrated) in Electrical and Electronics (Aug 2016 – Jun 2021)

• ✅ Machine Learning Specialization – Stanford University & Deeplearning.ai (Andrew Ng)
  • Comprehensive coursework in supervised/unsupervised learning, neural networks, and ML best practices
• ✅ Generative AI for Software Developers – IBM
  • Practical applications of GenAI in software engineering workflows
• ✅ Introduction to Generative AI – Google Cloud
  • Core concepts and cloud deployment of GenAI solutions

• 🏅 Right Brigade Award (Axtria) – Recognized for exemplary display of "RIGHT" values: Responsiveness, Integrity, Get going, Humble, and Team Player
• 🏅 Bravo Award (Axtria) – Honored for delivering high-quality work, exemplary performance, and strong client appreciation across multiple high-stakes projects

current_focus = {
    "research": [
        "Agentic AI Systems",
        "RAG Architectures & Vector Search", 
        "LLM Fine-Tuning & Inference Optimization",
        "Multi-Agent Coordination"
    ],
    "engineering": [
        "MLOps Pipelines & Automation",
        "System Architecture & API Design",
        "Optimization Algorithms (COBYLA, SLSQP, CCSA)",
        "Real-time Model Serving"
    ],
    "business": [
        "Marketing Mix Modeling (MMM)",
        "Portfolio Optimization", 
        "Product Leadership & Strategy",
        "Enterprise AI Solutions"
    ],
    "learning": [
        "Advanced AI/ML Research (UT Austin)",
        "Applied AI & Agentic Systems (IIIT Bangalore)",
        "Data Science Mastery (Deakin University)",
        "Distributed Computing & Cloud Architecture"
    ],
    "teaching": [
        "Training 70+ professionals",
        "Technical mentorship",
        "Knowledge sharing & documentation"
    ]
}

• Azure OpenAI integration and production deployment
• RAG system architecture with vector databases (FAISS, Pinecone, Weaviate)
• Prompt engineering and LLM fine-tuning
• Embeddings and semantic search optimization
• LangChain and LlamaIndex workflows

• Marketing Mix Modeling (MMM) with 25+ delivered projects
• Advanced optimization algorithms: COBYLA, SLSQP, CCSA
• Non-linear response curves (S-curves, diminishing returns)
• Portfolio-level optimization with multi-level constraints
• Budget planning and profit maximization scenarios

• Supervised learning: Random Forest, XGBoost, Logistic Regression
• Time series forecasting and anomaly detection
• Early adopter prediction and HCP targeting
• A/B testing, experiment design, and causal inference
• Model evaluation and hyperparameter optimization

• End-to-end pipeline automation with CI/CD
• Docker containerization and FastAPI deployment
• MLflow for experiment tracking and model versioning
• Cloud deployment: AWS, Azure, GCP, Databricks
• Performance optimization: 72% execution time reduction, 63% memory reduction

I'm always interested in:

• 🚀 Collaborating on AI/ML projects
• 💡 Discussing GenAI, LLMs, and optimization strategies
• 📚 Sharing knowledge on MLOps and production ML systems
• 🎯 Exploring opportunities in ML Engineering and AI Research

Reach out:

⭐️ From ananttripathi - Building the future of AI, one model at a time