class Aditi:
def __init__(self):
self.role = "Data Analyst & Gen AI Enthusiast"
self.education = "MCA (Data Science Specialization)"
self.focus = ["Data Analytics", "Business Intelligence", "Generative AI"]
self.currently_exploring = ["RAG Pipelines", "AWS for Analytics", "BigQuery Optimization"]
def philosophy(self):
return "Data becomes valuable only when it tells a story."
me = Aditi()- 🎓 MCA graduate specializing in Data Science, entering the analytics & Gen AI space with a portfolio of shipped, end-to-end projects
- 🧠 I turn messy datasets into dashboards, pipelines, and RAG-powered applications that answer real questions
- 🛠️ Skilled in SQL, Python, Power BI, BigQuery, and LangChain-based AI applications
- 📫 Reach me at aditipaitandy2003@gmail.com
Languages & Querying
Analytics & BI
Gen AI / ML
| 🔍 Extract | 🧹 Clean & Model | 📊 Visualize | 🤖 Apply AI |
|---|---|---|---|
| SQL, BigQuery, Python | Feature engineering, window functions, star schemas | Power BI, DAX, Looker Studio | RAG pipelines, LangChain, FAISS |
Open to collaborations, internships, and full-time opportunities in Data Analytics, BI, and Gen AI.
"Data becomes valuable only when it tells a story."