I’m a Data Scientist with 3+ years of experience building Machine Learning models, Generative AI workflows, Raman Spectroscopy analytics, calibration pipelines, and backend automation systems.
My work lies at the intersection of ML, signal processing, physics-based modeling, and device-level automation. I love solving analytical problems using a mix of domain knowledge + algorithms + experimentation.
- 🧪 Raman Spectroscopy Analytics
Peak detection, baseline correction, quantification, mixture analysis, calibration algorithms - 🤖 Machine Learning & Deep Learning
Classification, clustering, PCA, SVM, Random Forest, CNNs - 🧠 GenAI & LLMs
RAG, LangChain, FAISS, Embeddings, Gemini 1.5 Pro - ⚙️ Backend Automation
Python APIs, ETL workflows, data validation, reporting engines - 🧰 Research Paper Implementations
Converting academic algorithms into production-ready code
Languages: Python, SQL
ML Libraries: TensorFlow, Scikit-learn, SciPy, NumPy, Pandas
Visualization: Matplotlib, Plotly, Tableau
GenAI Tools: LangChain, FAISS, Embedding Models
Dev Tools: Git, VS Code, Jupyter, GCP
Other: Automation scripts, calibration modules, ETL pipelines
Backend for Raman preprocessing, calibration, peak extraction & quantification.
Automated manual-review workflow for ambiguous cases, reducing workload by 40%.
LLM-powered internal assistant using LangChain + FAISS + Gemini 1.5 Pro.
Automated device-level scan processing & calibration workflows.
- Improving spectral ML models using physics-informed features
- Building reliable calibration and drift-correction algorithms
- Experimenting with LLM-based automation & RAG workflows
- Contributing to open-source ML and signal processing tools
💼 LinkedIn: linkedin.com/in/ajay-kalaskar-a9781b178
📧 Email: ajay.kalaskar99@gmail.com
⭐ If you like my work, consider giving a star to the repositories you find useful!