class DataAnalyst(DataEngineer):
def __init__(self):
self.name = "Arun Pandian"
self.role = "Data Analyst | SDE"
self.location = "Tamil Nadu, India 🇮🇳"
self.core_stack = ["Python (Pandas/NumPy)", "Advanced SQL", "DAX"]
self.ecosystem = ["Power BI", "Tableau", "Snowflake", "BigQuery", "n8n"]
self.current = "Architecting Local LLM Automation & Real-time Metrics Streaming ⚙️"
def execute_workflow(self) -> str:
return "Transforming unstructured data into predictive, actionable intelligence. 📊"
def __repr__(self) -> str:
return f"<{self.name} | {self.role} | building in public>"
print(DataAnalyst().execute_workflow())
|
|
|
Reverse-engineered 90,000+ job postings utilizing advanced SQL Window Functions, CTEs, and cohort aggregations to decode the highest-ROI skill combinations for the modern tech stack.
|
Architected a DA-GRL framework on the CHB-MIT dataset implementing SHAP/LIME explainability for deep learning interoperability in healthcare AI (IEEE/Scopus publication pending).
|
|
Engineered an end-to-end API data ingestion pipeline using n8n and local GenAI models to automatically parse, score, and optimize resumes against live ATS metrics without compromising data privacy.
|
13+ enterprise-grade portfolio pipelines showcasing Power BI DAX optimization, Zero-Macro Excel Engineering, and actionable real-time BI deployment.
|
| 💻 Technical Domain | 📊 Proficiency | 🎯 Specialization |
|---|---|---|
Advanced SQL |
██████████ Advanced | Window Functions & CTEs |
Python (Pandas/EDA) |
█████████░ Advanced | Unstructured Data Normalization |
Power BI / DAX |
████████░░ Proficient | Interactive Data Storytelling |
Excel Architecture |
██████████ Advanced | Dynamic Arrays & Zero-Macro Build |
Snowflake / BigQuery |
█████░░░░░ Learning | Dimensional Data Modeling |
GenAI / Local LLM |
████████░░ Proficient | Privacy-first Automation (n8n) |
Swap these placeholders for your real credentials (e.g. Microsoft PL-300, Google Data Analytics, Snowflake SnowPro) — verified badges add real weight with recruiters.
