Headline

Data Analyst | SQL • Python • Power BI | ETL & Data Pipeline Development | Turning Raw Data into Business Insights | IIT Guwahati Certified in Data Science & AI

About

I help businesses turn raw, messy data into clear, actionable insights. With hands-on experience across financial and mobility datasets, I specialize in building end-to-end data pipelines — from raw ingestion and cleaning to interactive dashboards that drive decision-making. What I bring to the table: - Advanced SQL (CTEs, Window Functions, Joins, Subqueries) for high-volume, complex datasets - Python (Pandas, NumPy) for automated ETL pipelines that cut manual reporting effort - Power BI (DAX, Star Schema) — designed 15+ interactive dashboards tracking supply-demand and operational KPIs - Rigorous data QA — building sanitization protocols that reduce downstream errors in reporting and predictive modeling . Recent impact: - Optimized SQL queries to bring multi-gigabyte dataset processing down to seconds - Built Customer360, Order360, and Product360 models to uncover revenue drivers and customer segmentation patterns - Engineered dashboards analyzing 20-year market trends and ride-hailing "stress hours vs. golden hours". Currently deepening my expertise with an Advanced Certificate in Data Science & AI from IIT Guwahati. Always open to conversations about data, analytics, and how to make numbers tell better stories. Let's connect! 📧 rishavsinghrajput9934@gmail.com 💻 github.com/Rishav656

Location

Bengaluru

AI stack

claude code

claude

codex

deepmind

meta

openai

Work experience

Data Analyst at Billions United, May 2026 - Present · 5 mos, Bengaluru, Role Overview: As a Data Analyst Intern at Billion United, I served as a core member of the analytics team, taking end-to-end ownership of the data lifecycle. My mandate was to transform raw, fragmented data into high-fidelity assets that drive executive decision-making. I bridged the gap between complex technical infrastructure and strategic business needs by implementing rigorous data engineering standards and advanced analytical practices. Core Technical Competencies & Contributions: End-to-End Data Lifecycle Management: Spearheaded the full data lifecycle, from initial raw ingestion to final transformation. I established robust pipelines to intake unstructured data, applying meticulous cleaning and normalization techniques to curate high-fidelity datasets. This provided the foundation for reliable, executive-level business intelligence. Advanced SQL & Relational Database Engineering: Architected and executed multi-layered SQL queries to synthesize data from disparate sources. I leveraged advanced SQL functionality, including complex Joins, Window Functions, Aggregate Functions, and CTEs, to perform intricate data manipulation. My focus remained on query performance, writing index-aware scripts that maintained low latency even when processing massive, multi-gigabyte historical datasets. Rigorous Quality Assurance (QA) & Data Sanitization: Instituted a multi-stage data sanitization protocol to eliminate "data noise." By systematically identifying and rectifying missing records, resolving structural inconsistencies, and managing outliers, I ensured that all analytical outputs met the highest standards of integrity. This proactive QA framework significantly reduced downstream errors in predictive modeling and reporting dashboards. Strategic Data Mining & Performance Analysis: Applied sophisticated data mining methodologies to uncover latent operational patterns and systemic bottlenecks.

Data Analyst at AnalytixLabs, Aug 2025 - Apr 2026 · 9 mos, Bengaluru, •Designed relational database structure integrating company metadata and 25-year historical trading data for financial analysis. •Market Volatility Analytics: Developed complex SQL scripts to identify high-volatility trading periods by calculating daily price spreads (High vs. Low) and relative price categories (High/​Medium/​Low) using Subqueries and Aggregations. •Trend & Performance Attribution: Engineered a Power BI dashboard to visualize the "Quarterly Performance Cycle," enabling stakeholders to identify 20-year trends in stock closing prices and year-over-year growth metrics. •Advanced Query Optimization: Optimized data retrieval by implementing CTEs to find "Above-Average Trading Days," reducing query runtime for large-scale historical datasets and improving report latency. •Strategic KPI Reporting: Created automated logic to track Monthly Market Highs and Price Sensitivity, providing actionable insights into historical resistance levels and trading volume peaks.

Education

Adv.Cert.in Data Science & AI-BTCMP(IIT), Datat science, Indian Institute of Technology, Guwahati

BCA, Data Analyst, Aryabhatta Knowledge University, Patna

Public links

github: https://github.com/Rishav656

rishav656.github.io: https://rishav656.github.io/portfolio/