I’m an AI/ML Data Scientist with 6+ years of experience building end-to-end, business-critical data products - spanning predictive modeling, NLP, Generative AI, and LLM/Agentic AI systems. I hold a Master’s in Applied Data Science & Analytics (San José State University, CA). I’m passionate about turning messy, high-volume data into reliable, measurable, and production-ready solutions.
My journey into Data Science and AI has been driven by curiosity, strong problem ownership, and a desire to turn complex data into clear, measurable outcomes. Over 6+ years, I’ve built and improved solutions across Machine Learning, NLP, and Generative AI - ranging from predictive modeling and large-scale analytics to automation and decision intelligence.
I hold a Master’s in Applied Data Science & Analytics from San José State University. My experience spans both startups and big corporates, where I’ve delivered end-to-end ML work: framing ambiguous problems, engineering robust features, training and tuning models, and deploying pipelines that support real business workflows. More recently, I’ve been focused on LLM-powered systems, including RAG and agentic workflows using frameworks like LangChain/LangGraph, with an emphasis on reliability, grounded outputs, and practical adoption.
I specialize in building high-performing ML systems (supervised/unsupervised learning, tree-based models like XGBoost/Random Forest), NLP solutions (transformers, embeddings, RAG, prompt engineering), deep learning approaches (CNNs/RNNs/LSTMs), and Large Language Models (OpenAI, Gemini, Hugging Face, LangChain frameworks) where they add real value. I care deeply about explainability, evaluation, and iteration-making models not only accurate, but also interpretable, consistent, and production ready.
I am passionate about applying AI to solve real-world problems, optimizing predictive models, and enhancing explainability in ML systems. I thrive on building scalable AI solutions, improving LLM consistency, and integrating cutting-edge AI techniques into business strategies.
Let’s connect! I’m always open to collaborations, discussions, and innovative AI-driven projects. Check out my GitHub for my latest work, or reach out via LinkedIn or via email ravjot313@gmail.com.
- Statistical Programming Language:
PythonNumpyPandasSciPy,R - Machine Learning and Deep Learning Frameworks:
Scikit-LearnPyTorchTensorflow - Cloud and Databases:
AWSGoogle GCPMicrosoft AzureSQL ServerMySQLBigQuery - Data Visualization Tools:
MatplotlibSeabornTableauPowerBILookerGoogle Analytics - AI Prowess:
Large Language Models (LLMs)Retrieval Augmented Systems (RAGs)Fine-TuningGenerative AIAgentic AITransformersLangChainGPTsHuggingFaceGeminiLlamaWhisperAIBERTRoBERTaBARTLangGraphGroqOpenAIDiffusion ModelsGANsCGANsStyleGANs - Machine Learning:
Supervised LearningUnsupervised LearningRegressionClassificationRandom ForestXGBoostEnsemble Learning - Natural Language Processing (NLP):
NLTKSpaCyEmbedding Models - Deep Learning:
ANNsCNNsRNNsLSTMsGRUs
-
Programming Languages:
-
Machine Learning Frameworks:
-
Cloud Platforms:
-
Data Science & NLP Libraries:
-
AI
-
Data Visulization:
- Advanced deep learning techniques
- Real-time data streaming and processing
- Deployment of AI models using Docker & Kubernetes
- Building efficient NLP pipelines with Hugging Face and LangChain
Feel free to reach out to me through via email or any of the following platforms:
- Email: ravjot313@gmail.com
- LinkedIn: Ravjot Singh
- GitHub: Ravjot Singh
- Medium: Ravjot's Blog
Thank you for visiting my GitHub! 😄